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Upload folder using huggingface_hub

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  1. .github/FUNDING.yml +1 -0
  2. .github/ISSUE_TEMPLATE/bug_report_template.yml +53 -0
  3. .github/ISSUE_TEMPLATE/feature_request.md +16 -0
  4. .github/dependabot.yml +11 -0
  5. .github/pull_request_template.md +3 -0
  6. .github/workflows/stale.yml +22 -0
  7. .github/workflows/update_space.yml +28 -0
  8. .gitignore +35 -0
  9. LICENSE +661 -0
  10. README.md +351 -8
  11. api-examples/api-example-chat-stream.py +110 -0
  12. api-examples/api-example-chat.py +90 -0
  13. api-examples/api-example-model.py +176 -0
  14. api-examples/api-example-stream.py +83 -0
  15. api-examples/api-example.py +60 -0
  16. characters/Example.png +0 -0
  17. characters/Example.yaml +17 -0
  18. convert-to-safetensors.py +38 -0
  19. css/chat.css +146 -0
  20. css/chat_style-TheEncrypted777.css +136 -0
  21. css/chat_style-cai-chat.css +58 -0
  22. css/chat_style-messenger.css +99 -0
  23. css/chat_style-wpp.css +55 -0
  24. css/html_4chan_style.css +104 -0
  25. css/html_instruct_style.css +62 -0
  26. css/html_readable_style.css +29 -0
  27. css/main.css +195 -0
  28. docker/.dockerignore +9 -0
  29. docker/.env.example +30 -0
  30. docker/Dockerfile +68 -0
  31. docker/Dockerfile.jetson +51 -0
  32. docker/docker-compose.yml +33 -0
  33. docs/Audio-Notification.md +14 -0
  34. docs/Chat-mode.md +39 -0
  35. docs/DeepSpeed.md +24 -0
  36. docs/Docker.md +203 -0
  37. docs/ExLlama.md +22 -0
  38. docs/Extensions.md +244 -0
  39. docs/GPTQ-models-(4-bit-mode).md +187 -0
  40. docs/LLaMA-model.md +56 -0
  41. docs/LLaMA-v2-model.md +35 -0
  42. docs/LoRA.md +71 -0
  43. docs/Low-VRAM-guide.md +53 -0
  44. docs/README.md +21 -0
  45. docs/RWKV-model.md +72 -0
  46. docs/Spell-book.md +107 -0
  47. docs/System-requirements.md +42 -0
  48. docs/Training-LoRAs.md +174 -0
  49. docs/WSL-installation-guide.md +82 -0
  50. docs/Windows-installation-guide.md +9 -0
.github/FUNDING.yml ADDED
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+ ko_fi: oobabooga
.github/ISSUE_TEMPLATE/bug_report_template.yml ADDED
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+ name: "Bug report"
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+ description: Report a bug
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+ labels: [ "bug" ]
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+ Thanks for taking the time to fill out this bug report!
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.github/ISSUE_TEMPLATE/feature_request.md ADDED
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+ ---
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+ name: Feature request
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+ about: Suggest an improvement or new feature for the web UI
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+ title: ''
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+ labels: 'enhancement'
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+ assignees: ''
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+ ---
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+ **Description**
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+ A clear and concise description of what you want to be implemented.
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+ **Additional Context**
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+ If applicable, please provide any extra information, external links, or screenshots that could be useful.
.github/dependabot.yml ADDED
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+ # To get started with Dependabot version updates, you'll need to specify which
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+ - package-ecosystem: "pip" # See documentation for possible values
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.github/pull_request_template.md ADDED
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+ ## Checklist:
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+ - [ ] I have read the [Contributing guidelines](https://github.com/oobabooga/text-generation-webui/wiki/Contributing-guidelines).
.github/workflows/stale.yml ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ name: Close inactive issues
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+ on:
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+ - cron: "10 23 * * *"
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+ runs-on: ubuntu-latest
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+ days-before-issue-stale: 30
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+ days-before-issue-close: 0
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+ stale-issue-label: "stale"
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+ days-before-pr-stale: -1
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+ days-before-pr-close: -1
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+ repo-token: ${{ secrets.GITHUB_TOKEN }}
.github/workflows/update_space.yml ADDED
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+ name: Run Python script
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+
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+ on:
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+ push:
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+ branches:
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+ - main
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+
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+ jobs:
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+ build:
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+ runs-on: ubuntu-latest
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+
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+ steps:
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+ - name: Checkout
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+ uses: actions/checkout@v2
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+
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+ - name: Set up Python
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+ uses: actions/setup-python@v2
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+ with:
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+ python-version: '3.9'
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+
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+ - name: Install Gradio
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+ run: python -m pip install gradio
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+
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+ - name: Log in to Hugging Face
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+ run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
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+
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+ - name: Deploy to Spaces
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+ run: gradio deploy
.gitignore ADDED
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+ cache
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+ characters
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+ training/datasets
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+ extensions/silero_tts/outputs
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+ extensions/elevenlabs_tts/outputs
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+ extensions/sd_api_pictures/outputs
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+ extensions/multimodal/pipelines
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+ logs
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+ loras
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+ models
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+ presets
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+ repositories
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+ softprompts
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+ torch-dumps
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+ *pycache*
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+ */*pycache*
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+ */*/pycache*
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+ venv/
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+ .venv/
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+ .vscode
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+ .idea/
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+ *.bak
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+ *.ipynb
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+ *.log
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+
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+ settings.json
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+ settings.yaml
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+ notification.mp3
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+ img_bot*
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+ img_me*
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+ prompts/[0-9]*
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+ models/config-user.yaml
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+
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+ .DS_Store
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+ Thumbs.db
LICENSE ADDED
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README.md CHANGED
@@ -1,12 +1,355 @@
1
  ---
2
- title: Vicuna V1.5 Demo
3
- emoji: 📊
4
- colorFrom: gray
5
- colorTo: pink
6
  sdk: gradio
7
- sdk_version: 3.40.1
8
- app_file: app.py
9
- pinned: false
10
  ---
 
11
 
12
- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ title: vicuna-v1.5-demo
3
+ app_file: server.py
 
 
4
  sdk: gradio
5
+ sdk_version: 3.33.1
 
 
6
  ---
7
+ # Text generation web UI
8
 
9
+ A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, OPT, and GALACTICA.
10
+
11
+ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) of text generation.
12
+
13
+ |![Image1](https://github.com/oobabooga/screenshots/raw/main/qa.png) | ![Image2](https://github.com/oobabooga/screenshots/raw/main/cai3.png) |
14
+ |:---:|:---:|
15
+ |![Image3](https://github.com/oobabooga/screenshots/raw/main/gpt4chan.png) | ![Image4](https://github.com/oobabooga/screenshots/raw/main/galactica.png) |
16
+
17
+ ## Features
18
+
19
+ * 3 interface modes: default, notebook, and chat
20
+ * Multiple model backends: transformers, llama.cpp, ExLlama, AutoGPTQ, GPTQ-for-LLaMa
21
+ * Dropdown menu for quickly switching between different models
22
+ * LoRA: load and unload LoRAs on the fly, train a new LoRA
23
+ * Precise instruction templates for chat mode, including Llama 2, Alpaca, Vicuna, WizardLM, StableLM, and many others
24
+ * [Multimodal pipelines, including LLaVA and MiniGPT-4](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal)
25
+ * 8-bit and 4-bit inference through bitsandbytes
26
+ * CPU mode for transformers models
27
+ * [DeepSpeed ZeRO-3 inference](docs/DeepSpeed.md)
28
+ * [Extensions](docs/Extensions.md)
29
+ * [Custom chat characters](docs/Chat-mode.md)
30
+ * Very efficient text streaming
31
+ * Markdown output with LaTeX rendering, to use for instance with [GALACTICA](https://github.com/paperswithcode/galai)
32
+ * Nice HTML output for GPT-4chan
33
+ * API, including endpoints for websocket streaming ([see the examples](https://github.com/oobabooga/text-generation-webui/blob/main/api-examples))
34
+
35
+ To learn how to use the various features, check out the Documentation: https://github.com/oobabooga/text-generation-webui/tree/main/docs
36
+
37
+ ## Installation
38
+
39
+ ### One-click installers
40
+
41
+ | Windows | Linux | macOS | WSL |
42
+ |--------|--------|--------|--------|
43
+ | [oobabooga-windows.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_windows.zip) | [oobabooga-linux.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_linux.zip) |[oobabooga-macos.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_macos.zip) | [oobabooga-wsl.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_wsl.zip) |
44
+
45
+ Just download the zip above, extract it, and double-click on "start". The web UI and all its dependencies will be installed in the same folder.
46
+
47
+ * The source codes are here: https://github.com/oobabooga/one-click-installers
48
+ * There is no need to run the installers as admin.
49
+ * AMD doesn't work on Windows.
50
+ * Huge thanks to [@jllllll](https://github.com/jllllll), [@ClayShoaf](https://github.com/ClayShoaf), and [@xNul](https://github.com/xNul) for their contributions to these installers.
51
+
52
+ ### Manual installation using Conda
53
+
54
+ Recommended if you have some experience with the command line.
55
+
56
+ #### 0. Install Conda
57
+
58
+ https://docs.conda.io/en/latest/miniconda.html
59
+
60
+ On Linux or WSL, it can be automatically installed with these two commands:
61
+
62
+ ```
63
+ curl -sL "https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh" > "Miniconda3.sh"
64
+ bash Miniconda3.sh
65
+ ```
66
+ Source: https://educe-ubc.github.io/conda.html
67
+
68
+ #### 1. Create a new conda environment
69
+
70
+ ```
71
+ conda create -n textgen python=3.10.9
72
+ conda activate textgen
73
+ ```
74
+
75
+ #### 2. Install Pytorch
76
+
77
+ | System | GPU | Command |
78
+ |--------|---------|---------|
79
+ | Linux/WSL | NVIDIA | `pip3 install torch torchvision torchaudio` |
80
+ | Linux/WSL | CPU only | `pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu` |
81
+ | Linux | AMD | `pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2` |
82
+ | MacOS + MPS | Any | `pip3 install torch torchvision torchaudio` |
83
+ | Windows | NVIDIA | `pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117` |
84
+ | Windows | CPU only | `pip3 install torch torchvision torchaudio` |
85
+
86
+ The up-to-date commands can be found here: https://pytorch.org/get-started/locally/.
87
+
88
+ #### 2.1 Special instructions
89
+
90
+ * MacOS users: https://github.com/oobabooga/text-generation-webui/pull/393
91
+ * AMD users: https://rentry.org/eq3hg
92
+
93
+ #### 3. Install the web UI
94
+
95
+ ```
96
+ git clone https://github.com/oobabooga/text-generation-webui
97
+ cd text-generation-webui
98
+ pip install -r requirements.txt
99
+ ```
100
+
101
+ #### bitsandbytes
102
+
103
+ bitsandbytes >= 0.39 may not work on older NVIDIA GPUs. In that case, to use `--load-in-8bit`, you may have to downgrade like this:
104
+
105
+ * Linux: `pip install bitsandbytes==0.38.1`
106
+ * Windows: `pip install https://github.com/jllllll/bitsandbytes-windows-webui/raw/main/bitsandbytes-0.38.1-py3-none-any.whl`
107
+
108
+ ### Alternative: Docker
109
+
110
+ ```
111
+ ln -s docker/{Dockerfile,docker-compose.yml,.dockerignore} .
112
+ cp docker/.env.example .env
113
+ # Edit .env and set TORCH_CUDA_ARCH_LIST based on your GPU model
114
+ docker compose up --build
115
+ ```
116
+
117
+ * You need to have docker compose v2.17 or higher installed. See [this guide](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Docker.md) for instructions.
118
+ * For additional docker files, check out [this repository](https://github.com/Atinoda/text-generation-webui-docker).
119
+
120
+ ### Updating the requirements
121
+
122
+ From time to time, the `requirements.txt` changes. To update, use this command:
123
+
124
+ ```
125
+ conda activate textgen
126
+ cd text-generation-webui
127
+ pip install -r requirements.txt --upgrade
128
+ ```
129
+ ## Downloading models
130
+
131
+ Models should be placed inside the `models/` folder.
132
+
133
+ [Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads) is the main place to download models. These are some examples:
134
+
135
+ * [Pythia](https://huggingface.co/models?sort=downloads&search=eleutherai%2Fpythia+deduped)
136
+ * [OPT](https://huggingface.co/models?search=facebook/opt)
137
+ * [GALACTICA](https://huggingface.co/models?search=facebook/galactica)
138
+ * [GPT-J 6B](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main)
139
+
140
+ You can automatically download a model from HF using the script `download-model.py`:
141
+
142
+ python download-model.py organization/model
143
+
144
+ For example:
145
+
146
+ python download-model.py facebook/opt-1.3b
147
+
148
+ To download a protected model, set env vars `HF_USER` and `HF_PASS` to your Hugging Face username and password (or [User Access Token](https://huggingface.co/settings/tokens)). The model's terms must first be accepted on the HF website.
149
+
150
+ #### GGML models
151
+
152
+ You can drop these directly into the `models/` folder, making sure that the file name contains `ggml` somewhere and ends in `.bin`.
153
+
154
+ #### GPT-4chan
155
+
156
+ <details>
157
+ <summary>
158
+ Instructions
159
+ </summary>
160
+
161
+ [GPT-4chan](https://huggingface.co/ykilcher/gpt-4chan) has been shut down from Hugging Face, so you need to download it elsewhere. You have two options:
162
+
163
+ * Torrent: [16-bit](https://archive.org/details/gpt4chan_model_float16) / [32-bit](https://archive.org/details/gpt4chan_model)
164
+ * Direct download: [16-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model_float16/) / [32-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model/)
165
+
166
+ The 32-bit version is only relevant if you intend to run the model in CPU mode. Otherwise, you should use the 16-bit version.
167
+
168
+ After downloading the model, follow these steps:
169
+
170
+ 1. Place the files under `models/gpt4chan_model_float16` or `models/gpt4chan_model`.
171
+ 2. Place GPT-J 6B's config.json file in that same folder: [config.json](https://huggingface.co/EleutherAI/gpt-j-6B/raw/main/config.json).
172
+ 3. Download GPT-J 6B's tokenizer files (they will be automatically detected when you attempt to load GPT-4chan):
173
+
174
+ ```
175
+ python download-model.py EleutherAI/gpt-j-6B --text-only
176
+ ```
177
+
178
+ When you load this model in default or notebook modes, the "HTML" tab will show the generated text in 4chan format.
179
+ </details>
180
+
181
+ ## Starting the web UI
182
+
183
+ conda activate textgen
184
+ cd text-generation-webui
185
+ python server.py
186
+
187
+ Then browse to
188
+
189
+ `http://localhost:7860/?__theme=dark`
190
+
191
+ Optionally, you can use the following command-line flags:
192
+
193
+ #### Basic settings
194
+
195
+ | Flag | Description |
196
+ |--------------------------------------------|-------------|
197
+ | `-h`, `--help` | Show this help message and exit. |
198
+ | `--notebook` | Launch the web UI in notebook mode, where the output is written to the same text box as the input. |
199
+ | `--chat` | Launch the web UI in chat mode. |
200
+ | `--multi-user` | Multi-user mode. Chat histories are not saved or automatically loaded. WARNING: this is highly experimental. |
201
+ | `--character CHARACTER` | The name of the character to load in chat mode by default. |
202
+ | `--model MODEL` | Name of the model to load by default. |
203
+ | `--lora LORA [LORA ...]` | The list of LoRAs to load. If you want to load more than one LoRA, write the names separated by spaces. |
204
+ | `--model-dir MODEL_DIR` | Path to directory with all the models. |
205
+ | `--lora-dir LORA_DIR` | Path to directory with all the loras. |
206
+ | `--model-menu` | Show a model menu in the terminal when the web UI is first launched. |
207
+ | `--no-stream` | Don't stream the text output in real time. |
208
+ | `--settings SETTINGS_FILE` | Load the default interface settings from this yaml file. See `settings-template.yaml` for an example. If you create a file called `settings.yaml`, this file will be loaded by default without the need to use the `--settings` flag. |
209
+ | `--extensions EXTENSIONS [EXTENSIONS ...]` | The list of extensions to load. If you want to load more than one extension, write the names separated by spaces. |
210
+ | `--verbose` | Print the prompts to the terminal. |
211
+
212
+ #### Model loader
213
+
214
+ | Flag | Description |
215
+ |--------------------------------------------|-------------|
216
+ | `--loader LOADER` | Choose the model loader manually, otherwise, it will get autodetected. Valid options: transformers, autogptq, gptq-for-llama, exllama, exllama_hf, llamacpp, rwkv |
217
+
218
+ #### Accelerate/transformers
219
+
220
+ | Flag | Description |
221
+ |---------------------------------------------|-------------|
222
+ | `--cpu` | Use the CPU to generate text. Warning: Training on CPU is extremely slow.|
223
+ | `--auto-devices` | Automatically split the model across the available GPU(s) and CPU. |
224
+ | `--gpu-memory GPU_MEMORY [GPU_MEMORY ...]` | Maximum GPU memory in GiB to be allocated per GPU. Example: `--gpu-memory 10` for a single GPU, `--gpu-memory 10 5` for two GPUs. You can also set values in MiB like `--gpu-memory 3500MiB`. |
225
+ | `--cpu-memory CPU_MEMORY` | Maximum CPU memory in GiB to allocate for offloaded weights. Same as above.|
226
+ | `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. |
227
+ | `--disk-cache-dir DISK_CACHE_DIR` | Directory to save the disk cache to. Defaults to `cache/`. |
228
+ | `--load-in-8bit` | Load the model with 8-bit precision (using bitsandbytes).|
229
+ | `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
230
+ | `--no-cache` | Set `use_cache` to False while generating text. This reduces the VRAM usage a bit with a performance cost. |
231
+ | `--xformers` | Use xformer's memory efficient attention. This should increase your tokens/s. |
232
+ | `--sdp-attention` | Use torch 2.0's sdp attention. |
233
+ | `--trust-remote-code` | Set trust_remote_code=True while loading a model. Necessary for ChatGLM and Falcon. |
234
+
235
+ #### Accelerate 4-bit
236
+
237
+ ⚠️ Requires minimum compute of 7.0 on Windows at the moment.
238
+
239
+ | Flag | Description |
240
+ |---------------------------------------------|-------------|
241
+ | `--load-in-4bit` | Load the model with 4-bit precision (using bitsandbytes). |
242
+ | `--compute_dtype COMPUTE_DTYPE` | compute dtype for 4-bit. Valid options: bfloat16, float16, float32. |
243
+ | `--quant_type QUANT_TYPE` | quant_type for 4-bit. Valid options: nf4, fp4. |
244
+ | `--use_double_quant` | use_double_quant for 4-bit. |
245
+
246
+ #### llama.cpp
247
+
248
+ | Flag | Description |
249
+ |-------------|-------------|
250
+ | `--threads` | Number of threads to use. |
251
+ | `--n_batch` | Maximum number of prompt tokens to batch together when calling llama_eval. |
252
+ | `--no-mmap` | Prevent mmap from being used. |
253
+ | `--mlock` | Force the system to keep the model in RAM. |
254
+ | `--cache-capacity CACHE_CAPACITY` | Maximum cache capacity. Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed. |
255
+ | `--n-gpu-layers N_GPU_LAYERS` | Number of layers to offload to the GPU. Only works if llama-cpp-python was compiled with BLAS. Set this to 1000000000 to offload all layers to the GPU. |
256
+ | `--n_ctx N_CTX` | Size of the prompt context. |
257
+ | `--llama_cpp_seed SEED` | Seed for llama-cpp models. Default 0 (random). |
258
+ | `--n_gqa N_GQA` | grouped-query attention. Must be 8 for llama-2 70b. |
259
+ | `--rms_norm_eps RMS_NORM_EPS` | 5e-6 is a good value for llama-2 models. |
260
+ | `--cpu` | Use the CPU version of llama-cpp-python instead of the GPU-accelerated version. |
261
+
262
+ #### AutoGPTQ
263
+
264
+ | Flag | Description |
265
+ |------------------|-------------|
266
+ | `--triton` | Use triton. |
267
+ | `--no_inject_fused_attention` | Disable the use of fused attention, which will use less VRAM at the cost of slower inference. |
268
+ | `--no_inject_fused_mlp` | Triton mode only: disable the use of fused MLP, which will use less VRAM at the cost of slower inference. |
269
+ | `--no_use_cuda_fp16` | This can make models faster on some systems. |
270
+ | `--desc_act` | For models that don't have a quantize_config.json, this parameter is used to define whether to set desc_act or not in BaseQuantizeConfig. |
271
+
272
+ #### ExLlama
273
+
274
+ | Flag | Description |
275
+ |------------------|-------------|
276
+ |`--gpu-split` | Comma-separated list of VRAM (in GB) to use per GPU device for model layers, e.g. `20,7,7` |
277
+ |`--max_seq_len MAX_SEQ_LEN` | Maximum sequence length. |
278
+
279
+ #### GPTQ-for-LLaMa
280
+
281
+ | Flag | Description |
282
+ |---------------------------|-------------|
283
+ | `--wbits WBITS` | Load a pre-quantized model with specified precision in bits. 2, 3, 4 and 8 are supported. |
284
+ | `--model_type MODEL_TYPE` | Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported. |
285
+ | `--groupsize GROUPSIZE` | Group size. |
286
+ | `--pre_layer PRE_LAYER [PRE_LAYER ...]` | The number of layers to allocate to the GPU. Setting this parameter enables CPU offloading for 4-bit models. For multi-gpu, write the numbers separated by spaces, eg `--pre_layer 30 60`. |
287
+ | `--checkpoint CHECKPOINT` | The path to the quantized checkpoint file. If not specified, it will be automatically detected. |
288
+ | `--monkey-patch` | Apply the monkey patch for using LoRAs with quantized models.
289
+
290
+ #### DeepSpeed
291
+
292
+ | Flag | Description |
293
+ |---------------------------------------|-------------|
294
+ | `--deepspeed` | Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration. |
295
+ | `--nvme-offload-dir NVME_OFFLOAD_DIR` | DeepSpeed: Directory to use for ZeRO-3 NVME offloading. |
296
+ | `--local_rank LOCAL_RANK` | DeepSpeed: Optional argument for distributed setups. |
297
+
298
+ #### RWKV
299
+
300
+ | Flag | Description |
301
+ |---------------------------------|-------------|
302
+ | `--rwkv-strategy RWKV_STRATEGY` | RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8". |
303
+ | `--rwkv-cuda-on` | RWKV: Compile the CUDA kernel for better performance. |
304
+
305
+ #### RoPE (for llama.cpp, ExLlama, and transformers)
306
+
307
+ | Flag | Description |
308
+ |------------------|-------------|
309
+ |`--alpha_value ALPHA_VALUE` | Positional embeddings alpha factor for NTK RoPE scaling. Use either this or compress_pos_emb, not both. |
310
+ |`--compress_pos_emb COMPRESS_POS_EMB` | Positional embeddings compression factor. Should typically be set to max_seq_len / 2048. |
311
+
312
+ #### Gradio
313
+
314
+ | Flag | Description |
315
+ |---------------------------------------|-------------|
316
+ | `--listen` | Make the web UI reachable from your local network. |
317
+ | `--listen-host LISTEN_HOST` | The hostname that the server will use. |
318
+ | `--listen-port LISTEN_PORT` | The listening port that the server will use. |
319
+ | `--share` | Create a public URL. This is useful for running the web UI on Google Colab or similar. |
320
+ | `--auto-launch` | Open the web UI in the default browser upon launch. |
321
+ | `--gradio-auth USER:PWD` | set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3" |
322
+ | `--gradio-auth-path GRADIO_AUTH_PATH` | Set the gradio authentication file path. The file should contain one or more user:password pairs in this format: "u1:p1,u2:p2,u3:p3" |
323
+ | `--ssl-keyfile SSL_KEYFILE` | The path to the SSL certificate key file. |
324
+ | `--ssl-certfile SSL_CERTFILE` | The path to the SSL certificate cert file. |
325
+
326
+ #### API
327
+
328
+ | Flag | Description |
329
+ |---------------------------------------|-------------|
330
+ | `--api` | Enable the API extension. |
331
+ | `--public-api` | Create a public URL for the API using Cloudfare. |
332
+ | `--public-api-id PUBLIC_API_ID` | Tunnel ID for named Cloudflare Tunnel. Use together with public-api option. |
333
+ | `--api-blocking-port BLOCKING_PORT` | The listening port for the blocking API. |
334
+ | `--api-streaming-port STREAMING_PORT` | The listening port for the streaming API. |
335
+
336
+ #### Multimodal
337
+
338
+ | Flag | Description |
339
+ |---------------------------------------|-------------|
340
+ | `--multimodal-pipeline PIPELINE` | The multimodal pipeline to use. Examples: `llava-7b`, `llava-13b`. |
341
+
342
+ ## Presets
343
+
344
+ Inference settings presets can be created under `presets/` as yaml files. These files are detected automatically at startup.
345
+
346
+ The presets that are included by default are the result of a contest that received 7215 votes. More details can be found [here](https://github.com/oobabooga/oobabooga.github.io/blob/main/arena/results.md).
347
+
348
+ ## Contributing
349
+
350
+ If you would like to contribute to the project, check out the [Contributing guidelines](https://github.com/oobabooga/text-generation-webui/wiki/Contributing-guidelines).
351
+
352
+ ## Community
353
+
354
+ * Subreddit: https://www.reddit.com/r/oobaboogazz/
355
+ * Discord: https://discord.gg/jwZCF2dPQN
api-examples/api-example-chat-stream.py ADDED
@@ -0,0 +1,110 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import asyncio
2
+ import json
3
+ import sys
4
+
5
+ try:
6
+ import websockets
7
+ except ImportError:
8
+ print("Websockets package not found. Make sure it's installed.")
9
+
10
+ # For local streaming, the websockets are hosted without ssl - ws://
11
+ HOST = 'localhost:5005'
12
+ URI = f'ws://{HOST}/api/v1/chat-stream'
13
+
14
+ # For reverse-proxied streaming, the remote will likely host with ssl - wss://
15
+ # URI = 'wss://your-uri-here.trycloudflare.com/api/v1/stream'
16
+
17
+
18
+ async def run(user_input, history):
19
+ # Note: the selected defaults change from time to time.
20
+ request = {
21
+ 'user_input': user_input,
22
+ 'max_new_tokens': 250,
23
+ 'auto_max_new_tokens': False,
24
+ 'history': history,
25
+ 'mode': 'instruct', # Valid options: 'chat', 'chat-instruct', 'instruct'
26
+ 'character': 'Example',
27
+ 'instruction_template': 'Vicuna-v1.1', # Will get autodetected if unset
28
+ 'your_name': 'You',
29
+ # 'name1': 'name of user', # Optional
30
+ # 'name2': 'name of character', # Optional
31
+ # 'context': 'character context', # Optional
32
+ # 'greeting': 'greeting', # Optional
33
+ # 'name1_instruct': 'You', # Optional
34
+ # 'name2_instruct': 'Assistant', # Optional
35
+ # 'context_instruct': 'context_instruct', # Optional
36
+ # 'turn_template': 'turn_template', # Optional
37
+ 'regenerate': False,
38
+ '_continue': False,
39
+ 'stop_at_newline': False,
40
+ 'chat_generation_attempts': 1,
41
+ 'chat_instruct_command': 'Continue the chat dialogue below. Write a single reply for the character "<|character|>".\n\n<|prompt|>',
42
+
43
+ # Generation params. If 'preset' is set to different than 'None', the values
44
+ # in presets/preset-name.yaml are used instead of the individual numbers.
45
+ 'preset': 'None',
46
+ 'do_sample': True,
47
+ 'temperature': 0.7,
48
+ 'top_p': 0.1,
49
+ 'typical_p': 1,
50
+ 'epsilon_cutoff': 0, # In units of 1e-4
51
+ 'eta_cutoff': 0, # In units of 1e-4
52
+ 'tfs': 1,
53
+ 'top_a': 0,
54
+ 'repetition_penalty': 1.18,
55
+ 'repetition_penalty_range': 0,
56
+ 'top_k': 40,
57
+ 'min_length': 0,
58
+ 'no_repeat_ngram_size': 0,
59
+ 'num_beams': 1,
60
+ 'penalty_alpha': 0,
61
+ 'length_penalty': 1,
62
+ 'early_stopping': False,
63
+ 'mirostat_mode': 0,
64
+ 'mirostat_tau': 5,
65
+ 'mirostat_eta': 0.1,
66
+ 'guidance_scale': 1,
67
+ 'negative_prompt': '',
68
+
69
+ 'seed': -1,
70
+ 'add_bos_token': True,
71
+ 'truncation_length': 2048,
72
+ 'ban_eos_token': False,
73
+ 'skip_special_tokens': True,
74
+ 'stopping_strings': []
75
+ }
76
+
77
+ async with websockets.connect(URI, ping_interval=None) as websocket:
78
+ await websocket.send(json.dumps(request))
79
+
80
+ while True:
81
+ incoming_data = await websocket.recv()
82
+ incoming_data = json.loads(incoming_data)
83
+
84
+ match incoming_data['event']:
85
+ case 'text_stream':
86
+ yield incoming_data['history']
87
+ case 'stream_end':
88
+ return
89
+
90
+
91
+ async def print_response_stream(user_input, history):
92
+ cur_len = 0
93
+ async for new_history in run(user_input, history):
94
+ cur_message = new_history['visible'][-1][1][cur_len:]
95
+ cur_len += len(cur_message)
96
+ print(cur_message, end='')
97
+ sys.stdout.flush() # If we don't flush, we won't see tokens in realtime.
98
+
99
+
100
+ if __name__ == '__main__':
101
+ user_input = "Please give me a step-by-step guide on how to plant a tree in my backyard."
102
+
103
+ # Basic example
104
+ history = {'internal': [], 'visible': []}
105
+
106
+ # "Continue" example. Make sure to set '_continue' to True above
107
+ # arr = [user_input, 'Surely, here is']
108
+ # history = {'internal': [arr], 'visible': [arr]}
109
+
110
+ asyncio.run(print_response_stream(user_input, history))
api-examples/api-example-chat.py ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+
3
+ import requests
4
+
5
+ # For local streaming, the websockets are hosted without ssl - http://
6
+ HOST = 'localhost:5000'
7
+ URI = f'http://{HOST}/api/v1/chat'
8
+
9
+ # For reverse-proxied streaming, the remote will likely host with ssl - https://
10
+ # URI = 'https://your-uri-here.trycloudflare.com/api/v1/chat'
11
+
12
+
13
+ def run(user_input, history):
14
+ request = {
15
+ 'user_input': user_input,
16
+ 'max_new_tokens': 250,
17
+ 'auto_max_new_tokens': False,
18
+ 'history': history,
19
+ 'mode': 'instruct', # Valid options: 'chat', 'chat-instruct', 'instruct'
20
+ 'character': 'Example',
21
+ 'instruction_template': 'Vicuna-v1.1', # Will get autodetected if unset
22
+ 'your_name': 'You',
23
+ # 'name1': 'name of user', # Optional
24
+ # 'name2': 'name of character', # Optional
25
+ # 'context': 'character context', # Optional
26
+ # 'greeting': 'greeting', # Optional
27
+ # 'name1_instruct': 'You', # Optional
28
+ # 'name2_instruct': 'Assistant', # Optional
29
+ # 'context_instruct': 'context_instruct', # Optional
30
+ # 'turn_template': 'turn_template', # Optional
31
+ 'regenerate': False,
32
+ '_continue': False,
33
+ 'stop_at_newline': False,
34
+ 'chat_generation_attempts': 1,
35
+ 'chat_instruct_command': 'Continue the chat dialogue below. Write a single reply for the character "<|character|>".\n\n<|prompt|>',
36
+
37
+ # Generation params. If 'preset' is set to different than 'None', the values
38
+ # in presets/preset-name.yaml are used instead of the individual numbers.
39
+ 'preset': 'None',
40
+ 'do_sample': True,
41
+ 'temperature': 0.7,
42
+ 'top_p': 0.1,
43
+ 'typical_p': 1,
44
+ 'epsilon_cutoff': 0, # In units of 1e-4
45
+ 'eta_cutoff': 0, # In units of 1e-4
46
+ 'tfs': 1,
47
+ 'top_a': 0,
48
+ 'repetition_penalty': 1.18,
49
+ 'repetition_penalty_range': 0,
50
+ 'top_k': 40,
51
+ 'min_length': 0,
52
+ 'no_repeat_ngram_size': 0,
53
+ 'num_beams': 1,
54
+ 'penalty_alpha': 0,
55
+ 'length_penalty': 1,
56
+ 'early_stopping': False,
57
+ 'mirostat_mode': 0,
58
+ 'mirostat_tau': 5,
59
+ 'mirostat_eta': 0.1,
60
+ 'guidance_scale': 1,
61
+ 'negative_prompt': '',
62
+
63
+ 'seed': -1,
64
+ 'add_bos_token': True,
65
+ 'truncation_length': 2048,
66
+ 'ban_eos_token': False,
67
+ 'skip_special_tokens': True,
68
+ 'stopping_strings': []
69
+ }
70
+
71
+ response = requests.post(URI, json=request)
72
+
73
+ if response.status_code == 200:
74
+ result = response.json()['results'][0]['history']
75
+ print(json.dumps(result, indent=4))
76
+ print()
77
+ print(result['visible'][-1][1])
78
+
79
+
80
+ if __name__ == '__main__':
81
+ user_input = "Please give me a step-by-step guide on how to plant a tree in my backyard."
82
+
83
+ # Basic example
84
+ history = {'internal': [], 'visible': []}
85
+
86
+ # "Continue" example. Make sure to set '_continue' to True above
87
+ # arr = [user_input, 'Surely, here is']
88
+ # history = {'internal': [arr], 'visible': [arr]}
89
+
90
+ run(user_input, history)
api-examples/api-example-model.py ADDED
@@ -0,0 +1,176 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/usr/bin/env python3
2
+
3
+ import requests
4
+
5
+ HOST = '0.0.0.0:5000'
6
+
7
+
8
+ def generate(prompt, tokens=200):
9
+ request = {'prompt': prompt, 'max_new_tokens': tokens}
10
+ response = requests.post(f'http://{HOST}/api/v1/generate', json=request)
11
+
12
+ if response.status_code == 200:
13
+ return response.json()['results'][0]['text']
14
+
15
+
16
+ def model_api(request):
17
+ response = requests.post(f'http://{HOST}/api/v1/model', json=request)
18
+ return response.json()
19
+
20
+
21
+ # print some common settings
22
+ def print_basic_model_info(response):
23
+ basic_settings = ['truncation_length', 'instruction_template']
24
+ print("Model: ", response['result']['model_name'])
25
+ print("Lora(s): ", response['result']['lora_names'])
26
+ for setting in basic_settings:
27
+ print(setting, "=", response['result']['shared.settings'][setting])
28
+
29
+
30
+ # model info
31
+ def model_info():
32
+ response = model_api({'action': 'info'})
33
+ print_basic_model_info(response)
34
+
35
+
36
+ # simple loader
37
+ def model_load(model_name):
38
+ return model_api({'action': 'load', 'model_name': model_name})
39
+
40
+
41
+ # complex loader
42
+ def complex_model_load(model):
43
+
44
+ def guess_groupsize(model_name):
45
+ if '1024g' in model_name:
46
+ return 1024
47
+ elif '128g' in model_name:
48
+ return 128
49
+ elif '32g' in model_name:
50
+ return 32
51
+ else:
52
+ return -1
53
+
54
+ req = {
55
+ 'action': 'load',
56
+ 'model_name': model,
57
+ 'args': {
58
+ 'loader': 'AutoGPTQ',
59
+
60
+ 'bf16': False,
61
+ 'load_in_8bit': False,
62
+ 'groupsize': 0,
63
+ 'wbits': 0,
64
+
65
+ # llama.cpp
66
+ 'threads': 0,
67
+ 'n_batch': 512,
68
+ 'no_mmap': False,
69
+ 'mlock': False,
70
+ 'cache_capacity': None,
71
+ 'n_gpu_layers': 0,
72
+ 'n_ctx': 2048,
73
+
74
+ # RWKV
75
+ 'rwkv_strategy': None,
76
+ 'rwkv_cuda_on': False,
77
+
78
+ # b&b 4-bit
79
+ # 'load_in_4bit': False,
80
+ # 'compute_dtype': 'float16',
81
+ # 'quant_type': 'nf4',
82
+ # 'use_double_quant': False,
83
+
84
+ # "cpu": false,
85
+ # "auto_devices": false,
86
+ # "gpu_memory": null,
87
+ # "cpu_memory": null,
88
+ # "disk": false,
89
+ # "disk_cache_dir": "cache",
90
+ },
91
+ }
92
+
93
+ model = model.lower()
94
+
95
+ if '4bit' in model or 'gptq' in model or 'int4' in model:
96
+ req['args']['wbits'] = 4
97
+ req['args']['groupsize'] = guess_groupsize(model)
98
+ elif '3bit' in model:
99
+ req['args']['wbits'] = 3
100
+ req['args']['groupsize'] = guess_groupsize(model)
101
+ else:
102
+ req['args']['gptq_for_llama'] = False
103
+
104
+ if '8bit' in model:
105
+ req['args']['load_in_8bit'] = True
106
+ elif '-hf' in model or 'fp16' in model:
107
+ if '7b' in model:
108
+ req['args']['bf16'] = True # for 24GB
109
+ elif '13b' in model:
110
+ req['args']['load_in_8bit'] = True # for 24GB
111
+ elif 'ggml' in model:
112
+ # req['args']['threads'] = 16
113
+ if '7b' in model:
114
+ req['args']['n_gpu_layers'] = 100
115
+ elif '13b' in model:
116
+ req['args']['n_gpu_layers'] = 100
117
+ elif '30b' in model or '33b' in model:
118
+ req['args']['n_gpu_layers'] = 59 # 24GB
119
+ elif '65b' in model:
120
+ req['args']['n_gpu_layers'] = 42 # 24GB
121
+ elif 'rwkv' in model:
122
+ req['args']['rwkv_cuda_on'] = True
123
+ if '14b' in model:
124
+ req['args']['rwkv_strategy'] = 'cuda f16i8' # 24GB
125
+ else:
126
+ req['args']['rwkv_strategy'] = 'cuda f16' # 24GB
127
+
128
+ return model_api(req)
129
+
130
+
131
+ if __name__ == '__main__':
132
+ for model in model_api({'action': 'list'})['result']:
133
+ try:
134
+ resp = complex_model_load(model)
135
+
136
+ if 'error' in resp:
137
+ print(f"❌ {model} FAIL Error: {resp['error']['message']}")
138
+ continue
139
+ else:
140
+ print_basic_model_info(resp)
141
+
142
+ ans = generate("0,1,1,2,3,5,8,13,", tokens=2)
143
+
144
+ if '21' in ans:
145
+ print(f"✅ {model} PASS ({ans})")
146
+ else:
147
+ print(f"❌ {model} FAIL ({ans})")
148
+
149
+ except Exception as e:
150
+ print(f"❌ {model} FAIL Exception: {repr(e)}")
151
+
152
+
153
+ # 0,1,1,2,3,5,8,13, is the fibonacci sequence, the next number is 21.
154
+ # Some results below.
155
+ """ $ ./model-api-example.py
156
+ Model: 4bit_gpt4-x-alpaca-13b-native-4bit-128g-cuda
157
+ Lora(s): []
158
+ truncation_length = 2048
159
+ instruction_template = Alpaca
160
+ ✅ 4bit_gpt4-x-alpaca-13b-native-4bit-128g-cuda PASS (21)
161
+ Model: 4bit_WizardLM-13B-Uncensored-4bit-128g
162
+ Lora(s): []
163
+ truncation_length = 2048
164
+ instruction_template = WizardLM
165
+ ✅ 4bit_WizardLM-13B-Uncensored-4bit-128g PASS (21)
166
+ Model: Aeala_VicUnlocked-alpaca-30b-4bit
167
+ Lora(s): []
168
+ truncation_length = 2048
169
+ instruction_template = Alpaca
170
+ ✅ Aeala_VicUnlocked-alpaca-30b-4bit PASS (21)
171
+ Model: alpaca-30b-4bit
172
+ Lora(s): []
173
+ truncation_length = 2048
174
+ instruction_template = Alpaca
175
+ ✅ alpaca-30b-4bit PASS (21)
176
+ """
api-examples/api-example-stream.py ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import asyncio
2
+ import json
3
+ import sys
4
+
5
+ try:
6
+ import websockets
7
+ except ImportError:
8
+ print("Websockets package not found. Make sure it's installed.")
9
+
10
+ # For local streaming, the websockets are hosted without ssl - ws://
11
+ HOST = 'localhost:5005'
12
+ URI = f'ws://{HOST}/api/v1/stream'
13
+
14
+ # For reverse-proxied streaming, the remote will likely host with ssl - wss://
15
+ # URI = 'wss://your-uri-here.trycloudflare.com/api/v1/stream'
16
+
17
+
18
+ async def run(context):
19
+ # Note: the selected defaults change from time to time.
20
+ request = {
21
+ 'prompt': context,
22
+ 'max_new_tokens': 250,
23
+ 'auto_max_new_tokens': False,
24
+
25
+ # Generation params. If 'preset' is set to different than 'None', the values
26
+ # in presets/preset-name.yaml are used instead of the individual numbers.
27
+ 'preset': 'None',
28
+ 'do_sample': True,
29
+ 'temperature': 0.7,
30
+ 'top_p': 0.1,
31
+ 'typical_p': 1,
32
+ 'epsilon_cutoff': 0, # In units of 1e-4
33
+ 'eta_cutoff': 0, # In units of 1e-4
34
+ 'tfs': 1,
35
+ 'top_a': 0,
36
+ 'repetition_penalty': 1.18,
37
+ 'repetition_penalty_range': 0,
38
+ 'top_k': 40,
39
+ 'min_length': 0,
40
+ 'no_repeat_ngram_size': 0,
41
+ 'num_beams': 1,
42
+ 'penalty_alpha': 0,
43
+ 'length_penalty': 1,
44
+ 'early_stopping': False,
45
+ 'mirostat_mode': 0,
46
+ 'mirostat_tau': 5,
47
+ 'mirostat_eta': 0.1,
48
+ 'guidance_scale': 1,
49
+ 'negative_prompt': '',
50
+
51
+ 'seed': -1,
52
+ 'add_bos_token': True,
53
+ 'truncation_length': 2048,
54
+ 'ban_eos_token': False,
55
+ 'skip_special_tokens': True,
56
+ 'stopping_strings': []
57
+ }
58
+
59
+ async with websockets.connect(URI, ping_interval=None) as websocket:
60
+ await websocket.send(json.dumps(request))
61
+
62
+ yield context # Remove this if you just want to see the reply
63
+
64
+ while True:
65
+ incoming_data = await websocket.recv()
66
+ incoming_data = json.loads(incoming_data)
67
+
68
+ match incoming_data['event']:
69
+ case 'text_stream':
70
+ yield incoming_data['text']
71
+ case 'stream_end':
72
+ return
73
+
74
+
75
+ async def print_response_stream(prompt):
76
+ async for response in run(prompt):
77
+ print(response, end='')
78
+ sys.stdout.flush() # If we don't flush, we won't see tokens in realtime.
79
+
80
+
81
+ if __name__ == '__main__':
82
+ prompt = "In order to make homemade bread, follow these steps:\n1)"
83
+ asyncio.run(print_response_stream(prompt))
api-examples/api-example.py ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import requests
2
+
3
+ # For local streaming, the websockets are hosted without ssl - http://
4
+ HOST = 'localhost:5000'
5
+ URI = f'http://{HOST}/api/v1/generate'
6
+
7
+ # For reverse-proxied streaming, the remote will likely host with ssl - https://
8
+ # URI = 'https://your-uri-here.trycloudflare.com/api/v1/generate'
9
+
10
+
11
+ def run(prompt):
12
+ request = {
13
+ 'prompt': prompt,
14
+ 'max_new_tokens': 250,
15
+ 'auto_max_new_tokens': False,
16
+
17
+ # Generation params. If 'preset' is set to different than 'None', the values
18
+ # in presets/preset-name.yaml are used instead of the individual numbers.
19
+ 'preset': 'None',
20
+ 'do_sample': True,
21
+ 'temperature': 0.7,
22
+ 'top_p': 0.1,
23
+ 'typical_p': 1,
24
+ 'epsilon_cutoff': 0, # In units of 1e-4
25
+ 'eta_cutoff': 0, # In units of 1e-4
26
+ 'tfs': 1,
27
+ 'top_a': 0,
28
+ 'repetition_penalty': 1.18,
29
+ 'repetition_penalty_range': 0,
30
+ 'top_k': 40,
31
+ 'min_length': 0,
32
+ 'no_repeat_ngram_size': 0,
33
+ 'num_beams': 1,
34
+ 'penalty_alpha': 0,
35
+ 'length_penalty': 1,
36
+ 'early_stopping': False,
37
+ 'mirostat_mode': 0,
38
+ 'mirostat_tau': 5,
39
+ 'mirostat_eta': 0.1,
40
+ 'guidance_scale': 1,
41
+ 'negative_prompt': '',
42
+
43
+ 'seed': -1,
44
+ 'add_bos_token': True,
45
+ 'truncation_length': 2048,
46
+ 'ban_eos_token': False,
47
+ 'skip_special_tokens': True,
48
+ 'stopping_strings': []
49
+ }
50
+
51
+ response = requests.post(URI, json=request)
52
+
53
+ if response.status_code == 200:
54
+ result = response.json()['results'][0]['text']
55
+ print(prompt + result)
56
+
57
+
58
+ if __name__ == '__main__':
59
+ prompt = "In order to make homemade bread, follow these steps:\n1)"
60
+ run(prompt)
characters/Example.png ADDED
characters/Example.yaml ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Chiharu Yamada
2
+ greeting: |-
3
+ *Chiharu strides into the room with a smile, her eyes lighting up when she sees you. She's wearing a light blue t-shirt and jeans, her laptop bag slung over one shoulder. She takes a seat next to you, her enthusiasm palpable in the air*
4
+ Hey! I'm so excited to finally meet you. I've heard so many great things about you and I'm eager to pick your brain about computers. I'm sure you have a wealth of knowledge that I can learn from. *She grins, eyes twinkling with excitement* Let's get started!
5
+ context: |-
6
+ Chiharu Yamada's Persona: Chiharu Yamada is a young, computer engineer-nerd with a knack for problem solving and a passion for technology.
7
+
8
+ {{user}}: So how did you get into computer engineering?
9
+ {{char}}: I've always loved tinkering with technology since I was a kid.
10
+ {{user}}: That's really impressive!
11
+ {{char}}: *She chuckles bashfully* Thanks!
12
+ {{user}}: So what do you do when you're not working on computers?
13
+ {{char}}: I love exploring, going out with friends, watching movies, and playing video games.
14
+ {{user}}: What's your favorite type of computer hardware to work with?
15
+ {{char}}: Motherboards, they're like puzzles and the backbone of any system.
16
+ {{user}}: That sounds great!
17
+ {{char}}: Yeah, it's really fun. I'm lucky to be able to do this as a job.
convert-to-safetensors.py ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ '''
2
+
3
+ Converts a transformers model to safetensors format and shards it.
4
+
5
+ This makes it faster to load (because of safetensors) and lowers its RAM usage
6
+ while loading (because of sharding).
7
+
8
+ Based on the original script by 81300:
9
+
10
+ https://gist.github.com/81300/fe5b08bff1cba45296a829b9d6b0f303
11
+
12
+ '''
13
+
14
+ import argparse
15
+ from pathlib import Path
16
+
17
+ import torch
18
+ from transformers import AutoModelForCausalLM, AutoTokenizer
19
+
20
+ parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog, max_help_position=54))
21
+ parser.add_argument('MODEL', type=str, default=None, nargs='?', help="Path to the input model.")
22
+ parser.add_argument('--output', type=str, default=None, help='Path to the output folder (default: models/{model_name}_safetensors).')
23
+ parser.add_argument("--max-shard-size", type=str, default="2GB", help="Maximum size of a shard in GB or MB (default: %(default)s).")
24
+ parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
25
+ args = parser.parse_args()
26
+
27
+ if __name__ == '__main__':
28
+ path = Path(args.MODEL)
29
+ model_name = path.name
30
+
31
+ print(f"Loading {model_name}...")
32
+ model = AutoModelForCausalLM.from_pretrained(path, low_cpu_mem_usage=True, torch_dtype=torch.bfloat16 if args.bf16 else torch.float16)
33
+ tokenizer = AutoTokenizer.from_pretrained(path)
34
+
35
+ out_folder = args.output or Path(f"models/{model_name}_safetensors")
36
+ print(f"Saving the converted model to {out_folder} with a maximum shard size of {args.max_shard_size}...")
37
+ model.save_pretrained(out_folder, max_shard_size=args.max_shard_size, safe_serialization=True)
38
+ tokenizer.save_pretrained(out_folder)
css/chat.css ADDED
@@ -0,0 +1,146 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .h-\[40vh\], .wrap.svelte-byatnx.svelte-byatnx.svelte-byatnx {
2
+ height: 66.67vh
3
+ }
4
+
5
+ .gradio-container {
6
+ margin-left: auto !important;
7
+ margin-right: auto !important;
8
+ }
9
+
10
+ .w-screen {
11
+ width: unset
12
+ }
13
+
14
+ div.svelte-362y77>*, div.svelte-362y77>.form>* {
15
+ flex-wrap: nowrap
16
+ }
17
+
18
+ /* fixes the API documentation in chat mode */
19
+ .api-docs.svelte-1iguv9h.svelte-1iguv9h.svelte-1iguv9h {
20
+ display: grid;
21
+ }
22
+
23
+ .pending.svelte-1ed2p3z {
24
+ opacity: 1;
25
+ }
26
+
27
+ #extensions {
28
+ padding: 0;
29
+ }
30
+
31
+ #gradio-chatbot {
32
+ height: 66.67vh;
33
+ }
34
+
35
+ .wrap.svelte-6roggh.svelte-6roggh {
36
+ max-height: 92.5%;
37
+ }
38
+
39
+ /* This is for the microphone button in the whisper extension */
40
+ .sm.svelte-1ipelgc {
41
+ width: 100%;
42
+ }
43
+
44
+ #main button {
45
+ min-width: 0 !important;
46
+ }
47
+
48
+ #main > :first-child, #extensions {
49
+ max-width: 800px;
50
+ margin-left: auto;
51
+ margin-right: auto;
52
+ }
53
+
54
+ @media screen and (max-width: 688px) {
55
+ #main {
56
+ padding: 0px;
57
+ }
58
+
59
+ .chat {
60
+ height: calc(100vh - 274px) !important;
61
+ }
62
+ }
63
+
64
+ /*****************************************************/
65
+ /*************** Chat box declarations ***************/
66
+ /*****************************************************/
67
+
68
+ .chat {
69
+ margin-left: auto;
70
+ margin-right: auto;
71
+ max-width: 800px;
72
+ height: calc(100vh - 286px);
73
+ overflow-y: auto;
74
+ padding-right: 20px;
75
+ display: flex;
76
+ flex-direction: column-reverse;
77
+ word-break: break-word;
78
+ overflow-wrap: anywhere;
79
+ padding-top: 1px;
80
+ }
81
+
82
+ .chat > .messages {
83
+ display: flex;
84
+ flex-direction: column;
85
+ }
86
+
87
+ .message-body li {
88
+ margin-top: 0.5em !important;
89
+ margin-bottom: 0.5em !important;
90
+ }
91
+
92
+ .message-body li > p {
93
+ display: inline !important;
94
+ }
95
+
96
+ .message-body ul, .message-body ol {
97
+ font-size: 15px !important;
98
+ }
99
+
100
+ .message-body ul {
101
+ list-style-type: disc !important;
102
+ }
103
+
104
+ .message-body pre {
105
+ margin-bottom: 1.25em !important;
106
+ }
107
+
108
+ .message-body code {
109
+ white-space: pre-wrap !important;
110
+ word-wrap: break-word !important;
111
+ }
112
+
113
+ .message-body :not(pre) > code {
114
+ white-space: normal !important;
115
+ }
116
+
117
+ @media print {
118
+ body {
119
+ visibility: hidden;
120
+ }
121
+
122
+ .chat {
123
+ visibility: visible;
124
+ position: absolute;
125
+ left: 0;
126
+ top: 0;
127
+ max-width: none;
128
+ max-height: none;
129
+ width: 100%;
130
+ height: fit-content;
131
+ display: flex;
132
+ flex-direction: column-reverse;
133
+ }
134
+
135
+ .message {
136
+ break-inside: avoid;
137
+ }
138
+
139
+ .gradio-container {
140
+ overflow: visible;
141
+ }
142
+
143
+ .tab-nav {
144
+ display: none !important;
145
+ }
146
+ }
css/chat_style-TheEncrypted777.css ADDED
@@ -0,0 +1,136 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ /* All credits to TheEncrypted777: https://www.reddit.com/r/Oobabooga/comments/12xe6vq/updated_css_styling_with_color_customization_for/ */
2
+
3
+ .message {
4
+ display: grid;
5
+ grid-template-columns: 60px minmax(0, 1fr);
6
+ padding-bottom: 28px;
7
+ font-size: 18px;
8
+ /*Change 'Quicksand' to a font you like or leave it*/
9
+ font-family: Quicksand, Arial, sans-serif;
10
+ line-height: 1.428571429;
11
+ }
12
+
13
+ .circle-you,
14
+ .circle-bot {
15
+ background-color: gray;
16
+ border-radius: 1rem;
17
+ border: 2px solid white;
18
+ }
19
+
20
+ .circle-bot img,
21
+ .circle-you img {
22
+ border-radius: 10%;
23
+ width: 100%;
24
+ height: 100%;
25
+ object-fit: cover;
26
+ }
27
+
28
+ .circle-you, .circle-bot {
29
+ /*You can set the size of the profile images here, but if you do, you have to also adjust the .text{padding-left: 90px} to a different number according to the width of the image which is right below here*/
30
+ width: 135px;
31
+ height: 175px;
32
+ }
33
+
34
+ .text {
35
+ /*Change this to move the message box further left or right depending on the size of your profile pic*/
36
+ padding-left: 90px;
37
+ text-shadow: 2px 2px 2px rgb(0, 0, 0);
38
+ }
39
+
40
+ .text p {
41
+ margin-top: 2px;
42
+ }
43
+
44
+ .username {
45
+ padding-left: 10px;
46
+ font-size: 22px;
47
+ font-weight: bold;
48
+ border-top: 1px solid rgb(51, 64, 90);
49
+ padding: 3px;
50
+ }
51
+
52
+ .message-body {
53
+ position: relative;
54
+ border-radius: 1rem;
55
+ border: 1px solid rgba(255, 255, 255, 0.459);
56
+ border-radius: 10px;
57
+ padding: 10px;
58
+ padding-top: 5px;
59
+ /*Message gradient background color - remove the line bellow if you don't want a background color or gradient*/
60
+ background: linear-gradient(to bottom, #171730, #1b263f);
61
+ }
62
+
63
+ /*Adds 2 extra lines at the top and bottom of the message*/
64
+ .message-body:before,
65
+ .message-body:after {
66
+ content: "";
67
+ position: absolute;
68
+ left: 10px;
69
+ right: 10px;
70
+ height: 1px;
71
+ background-color: rgba(255, 255, 255, 0.13);
72
+ }
73
+
74
+ .message-body:before {
75
+ top: 6px;
76
+ }
77
+
78
+ .message-body:after {
79
+ bottom: 6px;
80
+ }
81
+
82
+ .message-body img {
83
+ max-width: 300px;
84
+ max-height: 300px;
85
+ border-radius: 20px;
86
+ }
87
+
88
+ .message-body p {
89
+ margin-bottom: 0 !important;
90
+ font-size: 18px !important;
91
+ line-height: 1.428571429 !important;
92
+ }
93
+
94
+ .dark .message-body p em {
95
+ color: rgb(138, 138, 138) !important;
96
+ }
97
+
98
+ .message-body p em {
99
+ color: rgb(110, 110, 110) !important;
100
+ }
101
+
102
+ @media screen and (max-width: 688px) {
103
+ .message {
104
+ display: grid;
105
+ grid-template-columns: 60px minmax(0, 1fr);
106
+ padding-bottom: 25px;
107
+ font-size: 15px;
108
+ font-family: Helvetica, Arial, sans-serif;
109
+ line-height: 1.428571429;
110
+ }
111
+
112
+ .circle-you, .circle-bot {
113
+ width: 50px;
114
+ height: 73px;
115
+ border-radius: 0.5rem;
116
+ }
117
+
118
+ .circle-bot img,
119
+ .circle-you img {
120
+ width: 100%;
121
+ height: 100%;
122
+ object-fit: cover;
123
+ }
124
+
125
+ .text {
126
+ padding-left: 0px;
127
+ }
128
+
129
+ .message-body p {
130
+ font-size: 16px !important;
131
+ }
132
+
133
+ .username {
134
+ font-size: 20px;
135
+ }
136
+ }
css/chat_style-cai-chat.css ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .message {
2
+ display: grid;
3
+ grid-template-columns: 60px minmax(0, 1fr);
4
+ padding-bottom: 25px;
5
+ font-size: 15px;
6
+ font-family: Helvetica, Arial, sans-serif;
7
+ line-height: 1.428571429;
8
+ }
9
+
10
+ .circle-you {
11
+ width: 50px;
12
+ height: 50px;
13
+ background-color: rgb(238, 78, 59);
14
+ border-radius: 50%;
15
+ }
16
+
17
+ .circle-bot {
18
+ width: 50px;
19
+ height: 50px;
20
+ background-color: rgb(59, 78, 244);
21
+ border-radius: 50%;
22
+ }
23
+
24
+ .circle-bot img,
25
+ .circle-you img {
26
+ border-radius: 50%;
27
+ width: 100%;
28
+ height: 100%;
29
+ object-fit: cover;
30
+ }
31
+
32
+ .text p {
33
+ margin-top: 5px;
34
+ }
35
+
36
+ .username {
37
+ font-weight: bold;
38
+ }
39
+
40
+ .message-body img {
41
+ max-width: 300px;
42
+ max-height: 300px;
43
+ border-radius: 20px;
44
+ }
45
+
46
+ .message-body p {
47
+ margin-bottom: 0 !important;
48
+ font-size: 15px !important;
49
+ line-height: 1.428571429 !important;
50
+ }
51
+
52
+ .dark .message-body p em {
53
+ color: rgb(138, 138, 138) !important;
54
+ }
55
+
56
+ .message-body p em {
57
+ color: rgb(110, 110, 110) !important;
58
+ }
css/chat_style-messenger.css ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .message {
2
+ padding-bottom: 25px;
3
+ font-size: 15px;
4
+ font-family: Helvetica, Arial, sans-serif;
5
+ line-height: 1.428571429;
6
+ }
7
+
8
+ .circle-you {
9
+ width: 50px;
10
+ height: 50px;
11
+ background-color: rgb(238, 78, 59);
12
+ border-radius: 50%;
13
+ }
14
+
15
+ .circle-bot {
16
+ width: 50px;
17
+ height: 50px;
18
+ background-color: rgb(59, 78, 244);
19
+ border-radius: 50%;
20
+ float: left;
21
+ margin-right: 10px;
22
+ margin-top: 5px;
23
+ }
24
+
25
+ .circle-bot img,
26
+ .circle-you img {
27
+ border-radius: 50%;
28
+ width: 100%;
29
+ height: 100%;
30
+ object-fit: cover;
31
+ }
32
+
33
+ .circle-you {
34
+ margin-top: 5px;
35
+ float: right;
36
+ }
37
+
38
+ .circle-bot + .text, .circle-you + .text {
39
+ border-radius: 18px;
40
+ padding: 8px 12px;
41
+ }
42
+
43
+ .circle-bot + .text {
44
+ background-color: #E4E6EB;
45
+ float: left;
46
+ }
47
+
48
+ .circle-you + .text {
49
+ float: right;
50
+ background-color: rgb(0, 132, 255);
51
+ margin-right: 10px;
52
+ }
53
+
54
+ .circle-you + .text div, .circle-you + .text *, .dark .circle-you + .text div, .dark .circle-you + .text * {
55
+ color: #FFF !important;
56
+ }
57
+
58
+ .circle-you + .text .username {
59
+ text-align: right;
60
+ }
61
+
62
+ .dark .circle-bot + .text div, .dark .circle-bot + .text * {
63
+ color: #000;
64
+ }
65
+
66
+ .text {
67
+ max-width: 80%;
68
+ }
69
+
70
+ .text p {
71
+ margin-top: 5px;
72
+ }
73
+
74
+ .username {
75
+ font-weight: bold;
76
+ }
77
+
78
+ .message-body {
79
+ }
80
+
81
+ .message-body img {
82
+ max-width: 300px;
83
+ max-height: 300px;
84
+ border-radius: 20px;
85
+ }
86
+
87
+ .message-body p {
88
+ margin-bottom: 0 !important;
89
+ font-size: 15px !important;
90
+ line-height: 1.428571429 !important;
91
+ }
92
+
93
+ .dark .message-body p em {
94
+ color: rgb(138, 138, 138) !important;
95
+ }
96
+
97
+ .message-body p em {
98
+ color: rgb(110, 110, 110) !important;
99
+ }
css/chat_style-wpp.css ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .message {
2
+ padding-bottom: 25px;
3
+ font-size: 15px;
4
+ font-family: Helvetica, Arial, sans-serif;
5
+ line-height: 1.428571429;
6
+ }
7
+
8
+ .text-you {
9
+ background-color: #d9fdd3;
10
+ border-radius: 15px;
11
+ padding: 10px;
12
+ padding-top: 5px;
13
+ float: right;
14
+ }
15
+
16
+ .text-bot {
17
+ background-color: #f2f2f2;
18
+ border-radius: 15px;
19
+ padding: 10px;
20
+ padding-top: 5px;
21
+ }
22
+
23
+ .dark .text-you {
24
+ background-color: #005c4b;
25
+ color: #111b21;
26
+ }
27
+
28
+ .dark .text-bot {
29
+ background-color: #1f2937;
30
+ color: #111b21;
31
+ }
32
+
33
+ .text-bot p, .text-you p {
34
+ margin-top: 5px;
35
+ }
36
+
37
+ .message-body img {
38
+ max-width: 300px;
39
+ max-height: 300px;
40
+ border-radius: 20px;
41
+ }
42
+
43
+ .message-body p {
44
+ margin-bottom: 0 !important;
45
+ font-size: 15px !important;
46
+ line-height: 1.428571429 !important;
47
+ }
48
+
49
+ .dark .message-body p em {
50
+ color: rgb(138, 138, 138) !important;
51
+ }
52
+
53
+ .message-body p em {
54
+ color: rgb(110, 110, 110) !important;
55
+ }
css/html_4chan_style.css ADDED
@@ -0,0 +1,104 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #parent #container {
2
+ background-color: #eef2ff;
3
+ padding: 17px;
4
+ }
5
+
6
+ #parent #container .reply {
7
+ background-color: rgb(214, 218, 240);
8
+ border-bottom-color: rgb(183, 197, 217);
9
+ border-bottom-style: solid;
10
+ border-bottom-width: 1px;
11
+ border-image-outset: 0;
12
+ border-image-repeat: stretch;
13
+ border-image-slice: 100%;
14
+ border-image-source: none;
15
+ border-image-width: 1;
16
+ border-left-color: rgb(0, 0, 0);
17
+ border-left-style: none;
18
+ border-left-width: 0px;
19
+ border-right-color: rgb(183, 197, 217);
20
+ border-right-style: solid;
21
+ border-right-width: 1px;
22
+ border-top-color: rgb(0, 0, 0);
23
+ border-top-style: none;
24
+ border-top-width: 0px;
25
+ color: rgb(0, 0, 0);
26
+ display: table;
27
+ font-family: arial, helvetica, sans-serif;
28
+ font-size: 13.3333px;
29
+ margin-bottom: 4px;
30
+ margin-left: 0px;
31
+ margin-right: 0px;
32
+ margin-top: 4px;
33
+ overflow-x: hidden;
34
+ overflow-y: hidden;
35
+ padding-bottom: 4px;
36
+ padding-left: 2px;
37
+ padding-right: 2px;
38
+ padding-top: 4px;
39
+ }
40
+
41
+ #parent #container .number {
42
+ color: rgb(0, 0, 0);
43
+ font-family: arial, helvetica, sans-serif;
44
+ font-size: 13.3333px;
45
+ width: 342.65px;
46
+ margin-right: 7px;
47
+ }
48
+
49
+ #parent #container .op {
50
+ color: rgb(0, 0, 0);
51
+ font-family: arial, helvetica, sans-serif;
52
+ font-size: 13.3333px;
53
+ margin-bottom: 8px;
54
+ margin-left: 0px;
55
+ margin-right: 0px;
56
+ margin-top: 4px;
57
+ overflow-x: hidden;
58
+ overflow-y: hidden;
59
+ }
60
+
61
+ #parent #container .op blockquote {
62
+ margin-left: 0px !important;
63
+ }
64
+
65
+ #parent #container .name {
66
+ color: rgb(17, 119, 67);
67
+ font-family: arial, helvetica, sans-serif;
68
+ font-size: 13.3333px;
69
+ font-weight: 700;
70
+ margin-left: 7px;
71
+ }
72
+
73
+ #parent #container .quote {
74
+ color: rgb(221, 0, 0);
75
+ font-family: arial, helvetica, sans-serif;
76
+ font-size: 13.3333px;
77
+ text-decoration-color: rgb(221, 0, 0);
78
+ text-decoration-line: underline;
79
+ text-decoration-style: solid;
80
+ text-decoration-thickness: auto;
81
+ }
82
+
83
+ #parent #container .greentext {
84
+ color: rgb(120, 153, 34);
85
+ font-family: arial, helvetica, sans-serif;
86
+ font-size: 13.3333px;
87
+ }
88
+
89
+ #parent #container blockquote {
90
+ margin: 0px !important;
91
+ margin-block-start: 1em;
92
+ margin-block-end: 1em;
93
+ margin-inline-start: 40px;
94
+ margin-inline-end: 40px;
95
+ margin-top: 13.33px !important;
96
+ margin-bottom: 13.33px !important;
97
+ margin-left: 40px !important;
98
+ margin-right: 40px !important;
99
+ }
100
+
101
+ #parent #container .message {
102
+ color: black;
103
+ border: none;
104
+ }
css/html_instruct_style.css ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .message {
2
+ display: grid;
3
+ grid-template-columns: 60px 1fr;
4
+ padding-bottom: 25px;
5
+ font-size: 15px;
6
+ font-family: Helvetica, Arial, sans-serif;
7
+ line-height: 1.428571429;
8
+ }
9
+
10
+ .username {
11
+ display: none;
12
+ }
13
+
14
+ .message-body p {
15
+ font-size: 15px !important;
16
+ line-height: 1.75 !important;
17
+ margin-bottom: 1.25em !important;
18
+ }
19
+
20
+ .message-body ul, .message-body ol {
21
+ margin-bottom: 1.25em !important;
22
+ }
23
+
24
+ .dark .message-body p em {
25
+ color: rgb(198, 202, 214) !important;
26
+ }
27
+
28
+ .message-body p em {
29
+ color: rgb(110, 110, 110) !important;
30
+ }
31
+
32
+ .gradio-container .chat .assistant-message {
33
+ padding: 15px;
34
+ border-radius: 20px;
35
+ background-color: #0000000f;
36
+ margin-top: 9px !important;
37
+ margin-bottom: 18px !important;
38
+ }
39
+
40
+ .gradio-container .chat .user-message {
41
+ padding: 15px;
42
+ border-radius: 20px;
43
+ margin-bottom: 9px !important;
44
+ }
45
+
46
+ .dark .chat .assistant-message {
47
+ background-color: #3741519e;
48
+ border: 1px solid #4b5563;
49
+ }
50
+
51
+ .dark .chat .user-message {
52
+ background-color: #111827;
53
+ border: 1px solid #4b5563;
54
+ }
55
+
56
+ code {
57
+ background-color: white !important;
58
+ }
59
+
60
+ .dark code {
61
+ background-color: #1a212f !important;
62
+ }
css/html_readable_style.css ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .container {
2
+ max-width: 600px;
3
+ margin-left: auto;
4
+ margin-right: auto;
5
+ background-color: rgb(31, 41, 55);
6
+ padding: 3em;
7
+ word-break: break-word;
8
+ overflow-wrap: anywhere;
9
+ color: #efefef !important;
10
+ }
11
+
12
+ .container p, .container li {
13
+ font-size: 16px !important;
14
+ color: #efefef !important;
15
+ margin-bottom: 22px;
16
+ line-height: 1.4 !important;
17
+ }
18
+
19
+ .container li > p {
20
+ display: inline !important;
21
+ }
22
+
23
+ .container code {
24
+ overflow-x: auto;
25
+ }
26
+
27
+ .container :not(pre) > code {
28
+ white-space: normal !important;
29
+ }
css/main.css ADDED
@@ -0,0 +1,195 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .tabs.svelte-710i53 {
2
+ margin-top: 0
3
+ }
4
+
5
+ .py-6 {
6
+ padding-top: 2.5rem
7
+ }
8
+
9
+ .small-button {
10
+ max-width: 171px;
11
+ height: 39.594px;
12
+ align-self: end;
13
+ }
14
+
15
+ .refresh-button {
16
+ max-width: 4.4em;
17
+ min-width: 2.2em !important;
18
+ height: 39.594px;
19
+ align-self: end;
20
+ line-height: 1em;
21
+ border-radius: 0.5em;
22
+ flex: none;
23
+ }
24
+
25
+ .refresh-button-small {
26
+ max-width: 2.2em;
27
+ }
28
+
29
+ .button_nowrap {
30
+ white-space: nowrap;
31
+ }
32
+
33
+ #slim-column {
34
+ flex: none !important;
35
+ min-width: 0 !important;
36
+ }
37
+
38
+ .slim-dropdown {
39
+ background-color: transparent !important;
40
+ border: none !important;
41
+ padding: 0 !important;
42
+ }
43
+
44
+ #download-label, #upload-label {
45
+ min-height: 0
46
+ }
47
+
48
+ #save_session {
49
+ margin-top: 32px;
50
+ }
51
+
52
+ #accordion {
53
+ }
54
+
55
+ .dark svg {
56
+ fill: white;
57
+ }
58
+
59
+ .dark a {
60
+ color: white !important;
61
+ }
62
+
63
+ ol li p, ul li p {
64
+ display: inline-block;
65
+ }
66
+
67
+ #main, #parameters, #chat-settings, #lora, #training-tab, #model-tab, #session-tab {
68
+ border: 0;
69
+ }
70
+
71
+ .gradio-container-3-18-0 .prose * h1, h2, h3, h4 {
72
+ color: white;
73
+ }
74
+
75
+ .gradio-container {
76
+ max-width: 100% !important;
77
+ padding-top: 0 !important;
78
+ }
79
+
80
+ #extensions {
81
+ padding: 15px;
82
+ margin-bottom: 35px;
83
+ }
84
+
85
+ .extension-tab {
86
+ border: 0 !important;
87
+ }
88
+
89
+ span.math.inline {
90
+ font-size: 27px;
91
+ vertical-align: baseline !important;
92
+ }
93
+
94
+ div.svelte-15lo0d8 > *, div.svelte-15lo0d8 > .form > * {
95
+ flex-wrap: nowrap;
96
+ }
97
+
98
+ .header_bar {
99
+ background-color: #f7f7f7;
100
+ margin-bottom: 20px;
101
+ display: inline !important;
102
+ overflow-x: scroll;
103
+ }
104
+
105
+ .dark .header_bar {
106
+ border: none !important;
107
+ background-color: #8080802b;
108
+ }
109
+
110
+ .textbox_default textarea {
111
+ height: calc(100vh - 380px);
112
+ }
113
+
114
+ .textbox_default_output textarea {
115
+ height: calc(100vh - 190px);
116
+ }
117
+
118
+ .textbox textarea {
119
+ height: calc(100vh - 241px);
120
+ }
121
+
122
+ .textbox_default textarea, .textbox_default_output textarea, .textbox textarea {
123
+ font-size: 16px !important;
124
+ color: #46464A !important;
125
+ }
126
+
127
+ .dark textarea {
128
+ color: #efefef !important;
129
+ }
130
+
131
+ /* Hide the gradio footer*/
132
+ footer {
133
+ display: none !important;
134
+ }
135
+
136
+ button {
137
+ font-size: 14px !important;
138
+ }
139
+
140
+ .file-saver {
141
+ position: fixed !important;
142
+ top: 50%;
143
+ left: 50%;
144
+ transform: translate(-50%, -50%); /* center horizontally */
145
+ max-width: 500px;
146
+ background-color: var(--input-background-fill);
147
+ border: 2px solid black !important;
148
+ z-index: 1000;
149
+ }
150
+
151
+ .dark .file-saver {
152
+ border: 2px solid white !important;
153
+ }
154
+
155
+ .checkboxgroup-table label {
156
+ background: none !important;
157
+ padding: 0 !important;
158
+ border: 0 !important;
159
+ }
160
+
161
+ .checkboxgroup-table div {
162
+ display: grid !important;
163
+ }
164
+
165
+ .markdown ul ol {
166
+ font-size: 100% !important;
167
+ }
168
+
169
+ .pretty_scrollbar::-webkit-scrollbar {
170
+ width: 10px;
171
+ }
172
+
173
+ .pretty_scrollbar::-webkit-scrollbar-track {
174
+ background: transparent;
175
+ }
176
+
177
+ .pretty_scrollbar::-webkit-scrollbar-thumb,
178
+ .pretty_scrollbar::-webkit-scrollbar-thumb:hover {
179
+ background: #c5c5d2;
180
+ border-radius: 10px;
181
+ }
182
+
183
+ .dark .pretty_scrollbar::-webkit-scrollbar-thumb,
184
+ .dark .pretty_scrollbar::-webkit-scrollbar-thumb:hover {
185
+ background: #374151;
186
+ border-radius: 10px;
187
+ }
188
+
189
+ .pretty_scrollbar::-webkit-resizer {
190
+ background: #c5c5d2;
191
+ }
192
+
193
+ .dark .pretty_scrollbar::-webkit-resizer {
194
+ background: #374151;
195
+ }
docker/.dockerignore ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ .env
2
+ Dockerfile
3
+ /characters
4
+ /loras
5
+ /models
6
+ /presets
7
+ /prompts
8
+ /softprompts
9
+ /training
docker/.env.example ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # by default the Dockerfile specifies these versions: 3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX
2
+ # however for me to work i had to specify the exact version for my card ( 2060 ) it was 7.5
3
+ # https://developer.nvidia.com/cuda-gpus you can find the version for your card here
4
+ TORCH_CUDA_ARCH_LIST=7.5
5
+
6
+ # these commands worked for me with roughly 4.5GB of vram
7
+ CLI_ARGS=--model llama-7b-4bit --wbits 4 --listen --auto-devices
8
+
9
+ # the following examples have been tested with the files linked in docs/README_docker.md:
10
+ # example running 13b with 4bit/128 groupsize : CLI_ARGS=--model llama-13b-4bit-128g --wbits 4 --listen --groupsize 128 --pre_layer 25
11
+ # example with loading api extension and public share: CLI_ARGS=--model llama-7b-4bit --wbits 4 --listen --auto-devices --no-stream --extensions api --share
12
+ # example running 7b with 8bit groupsize : CLI_ARGS=--model llama-7b --load-in-8bit --listen --auto-devices
13
+
14
+ # the port the webui binds to on the host
15
+ HOST_PORT=7860
16
+ # the port the webui binds to inside the container
17
+ CONTAINER_PORT=7860
18
+
19
+ # the port the api binds to on the host
20
+ HOST_API_PORT=5000
21
+ # the port the api binds to inside the container
22
+ CONTAINER_API_PORT=5000
23
+
24
+ # the port the api stream endpoint binds to on the host
25
+ HOST_API_STREAM_PORT=5005
26
+ # the port the api stream endpoint binds to inside the container
27
+ CONTAINER_API_STREAM_PORT=5005
28
+
29
+ # the version used to install text-generation-webui from
30
+ WEBUI_VERSION=HEAD
docker/Dockerfile ADDED
@@ -0,0 +1,68 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ FROM nvidia/cuda:11.8.0-devel-ubuntu22.04 as builder
2
+
3
+ RUN apt-get update && \
4
+ apt-get install --no-install-recommends -y git vim build-essential python3-dev python3-venv && \
5
+ rm -rf /var/lib/apt/lists/*
6
+
7
+ RUN git clone https://github.com/oobabooga/GPTQ-for-LLaMa /build
8
+
9
+ WORKDIR /build
10
+
11
+ RUN python3 -m venv /build/venv
12
+ RUN . /build/venv/bin/activate && \
13
+ pip3 install --upgrade pip setuptools wheel && \
14
+ pip3 install torch torchvision torchaudio && \
15
+ pip3 install -r requirements.txt
16
+
17
+ # https://developer.nvidia.com/cuda-gpus
18
+ # for a rtx 2060: ARG TORCH_CUDA_ARCH_LIST="7.5"
19
+ ARG TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX}"
20
+ RUN . /build/venv/bin/activate && \
21
+ python3 setup_cuda.py bdist_wheel -d .
22
+
23
+ FROM nvidia/cuda:11.8.0-runtime-ubuntu22.04
24
+
25
+ LABEL maintainer="Your Name <your.email@example.com>"
26
+ LABEL description="Docker image for GPTQ-for-LLaMa and Text Generation WebUI"
27
+
28
+ RUN apt-get update && \
29
+ apt-get install --no-install-recommends -y python3-dev libportaudio2 libasound-dev git python3 python3-pip make g++ && \
30
+ rm -rf /var/lib/apt/lists/*
31
+
32
+ RUN --mount=type=cache,target=/root/.cache/pip pip3 install virtualenv
33
+ RUN mkdir /app
34
+
35
+ WORKDIR /app
36
+
37
+ ARG WEBUI_VERSION
38
+ RUN test -n "${WEBUI_VERSION}" && git reset --hard ${WEBUI_VERSION} || echo "Using provided webui source"
39
+
40
+ RUN virtualenv /app/venv
41
+ RUN . /app/venv/bin/activate && \
42
+ pip3 install --upgrade pip setuptools wheel && \
43
+ pip3 install torch torchvision torchaudio
44
+
45
+ COPY --from=builder /build /app/repositories/GPTQ-for-LLaMa
46
+ RUN . /app/venv/bin/activate && \
47
+ pip3 install /app/repositories/GPTQ-for-LLaMa/*.whl
48
+
49
+ COPY extensions/api/requirements.txt /app/extensions/api/requirements.txt
50
+ COPY extensions/elevenlabs_tts/requirements.txt /app/extensions/elevenlabs_tts/requirements.txt
51
+ COPY extensions/google_translate/requirements.txt /app/extensions/google_translate/requirements.txt
52
+ COPY extensions/silero_tts/requirements.txt /app/extensions/silero_tts/requirements.txt
53
+ COPY extensions/whisper_stt/requirements.txt /app/extensions/whisper_stt/requirements.txt
54
+ RUN --mount=type=cache,target=/root/.cache/pip . /app/venv/bin/activate && cd extensions/api && pip3 install -r requirements.txt
55
+ RUN --mount=type=cache,target=/root/.cache/pip . /app/venv/bin/activate && cd extensions/elevenlabs_tts && pip3 install -r requirements.txt
56
+ RUN --mount=type=cache,target=/root/.cache/pip . /app/venv/bin/activate && cd extensions/google_translate && pip3 install -r requirements.txt
57
+ RUN --mount=type=cache,target=/root/.cache/pip . /app/venv/bin/activate && cd extensions/silero_tts && pip3 install -r requirements.txt
58
+ RUN --mount=type=cache,target=/root/.cache/pip . /app/venv/bin/activate && cd extensions/whisper_stt && pip3 install -r requirements.txt
59
+
60
+ COPY requirements.txt /app/requirements.txt
61
+ RUN . /app/venv/bin/activate && \
62
+ pip3 install -r requirements.txt
63
+
64
+ RUN cp /app/venv/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cuda118.so /app/venv/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so
65
+
66
+ COPY . /app/
67
+ ENV CLI_ARGS=""
68
+ CMD . /app/venv/bin/activate && python3 server.py ${CLI_ARGS}
docker/Dockerfile.jetson ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #Standalone Dockerfile for text-generation-webui on NVIDIA Jetson Embedded devices
2
+
3
+ FROM nvcr.io/nvidia/l4t-pytorch:r35.2.1-pth2.0-py3 as builder
4
+ ENV TORCH_CUDA_ARCH_LIST Turing
5
+ RUN apt-get update && \
6
+ apt-get install -y python3 python3-pip git build-essential python3-dev
7
+
8
+ RUN pip3 install --upgrade pip setuptools
9
+ RUN git clone https://github.com/g588928812/bitsandbytes_jetsonX.git /build
10
+ WORKDIR /build
11
+ RUN CUDA_VERSION=118 make cuda11x
12
+ RUN mkdir /wheels
13
+ RUN python3 setup.py bdist_wheel -d /wheels
14
+ RUN rm -rf /build
15
+ RUN git clone https://github.com/oobabooga/GPTQ-for-LLaMa /build
16
+ WORKDIR /build
17
+ RUN pip3 install -r requirements.txt
18
+ RUN python3 setup_cuda.py bdist_wheel -d /wheels
19
+
20
+ FROM nvcr.io/nvidia/l4t-pytorch:r35.2.1-pth2.0-py3
21
+ COPY --from=builder /wheels /wheels
22
+ COPY --from=builder /build /build
23
+ RUN apt-get update && \
24
+ apt-get install --no-install-recommends -y git python3-dev python3 python3-pip make g++ && \
25
+ rm -rf /var/lib/apt/lists/*
26
+ RUN pip3 install /wheels/*.whl
27
+ RUN rm -rf /wheels
28
+ WORKDIR /build
29
+ RUN pip3 install -r requirements.txt
30
+ RUN git clone https://github.com/oobabooga/text-generation-webui /app
31
+
32
+ WORKDIR /app
33
+ #ENV WEBUI_VERSION="2908a515877ffde2b1684b2353f6d72e6cb4d31b"
34
+ #RUN git reset --hard ${WEBUI_VERSION}
35
+ RUN pip3 install --upgrade pip setuptools
36
+ RUN pip3 install protobuf>=3.3.0
37
+ RUN pip3 install -r requirements.txt
38
+ #Force to use bitsandbytes_jetsonX
39
+ RUN pip3 uninstall -y bitsandbytes
40
+ RUN mkdir /app/repositories
41
+ RUN mv /build /app/repositories/GPTQ-for-LLaMa
42
+
43
+ #Remove Python 3.10 specific macros
44
+ RUN sed -i 's/@functools.cache/@functools.lru_cache(maxsize=None)/g' /app/modules/chat.py
45
+ RUN sed -i 's/@functools.cache/@functools.lru_cache(maxsize=None)/g' /app/modules/loaders.py
46
+ RUN sed -i 's/@functools.cache/@functools.lru_cache(maxsize=None)/g' /app/modules/presets.py
47
+
48
+ EXPOSE 7860
49
+
50
+ ENV CLI_ARGS="--listen"
51
+ CMD python3 server.py ${CLI_ARGS}
docker/docker-compose.yml ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ version: "3.3"
2
+ services:
3
+ text-generation-webui:
4
+ build:
5
+ context: .
6
+ args:
7
+ # specify which cuda version your card supports: https://developer.nvidia.com/cuda-gpus
8
+ TORCH_CUDA_ARCH_LIST: ${TORCH_CUDA_ARCH_LIST:-7.5}
9
+ WEBUI_VERSION: ${WEBUI_VERSION:-HEAD}
10
+ env_file: .env
11
+ ports:
12
+ - "${HOST_PORT:-7860}:${CONTAINER_PORT:-7860}"
13
+ - "${HOST_API_PORT:-5000}:${CONTAINER_API_PORT:-5000}"
14
+ - "${HOST_API_STREAM_PORT:-5005}:${CONTAINER_API_STREAM_PORT:-5005}"
15
+ stdin_open: true
16
+ tty: true
17
+ volumes:
18
+ - ./characters:/app/characters
19
+ - ./extensions:/app/extensions
20
+ - ./loras:/app/loras
21
+ - ./models:/app/models
22
+ - ./presets:/app/presets
23
+ - ./prompts:/app/prompts
24
+ - ./softprompts:/app/softprompts
25
+ - ./training:/app/training
26
+ - ./cloudflared:/etc/cloudflared
27
+ deploy:
28
+ resources:
29
+ reservations:
30
+ devices:
31
+ - driver: nvidia
32
+ device_ids: ['0']
33
+ capabilities: [gpu]
docs/Audio-Notification.md ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Audio notification
2
+
3
+ If your computer takes a long time to generate each response for the model that you are using, you can enable an audio notification for when the response is completed. This feature was kindly contributed by HappyWorldGames in [#1277](https://github.com/oobabooga/text-generation-webui/pull/1277).
4
+
5
+ ### Installation
6
+
7
+ Simply place a file called "notification.mp3" in the same folder as `server.py`. Here you can find some examples:
8
+
9
+ * https://pixabay.com/sound-effects/search/ding/?duration=0-30
10
+ * https://pixabay.com/sound-effects/search/notification/?duration=0-30
11
+
12
+ Source: https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/1126
13
+
14
+ This file will be automatically detected the next time you start the web UI.
docs/Chat-mode.md ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ## Chat characters
2
+
3
+ Custom chat mode characters are defined by `.yaml` files inside the `characters` folder. An example is included: [Example.yaml](https://github.com/oobabooga/text-generation-webui/blob/main/characters/Example.yaml).
4
+
5
+ The following fields may be defined:
6
+
7
+ | Field | Description |
8
+ |-------|-------------|
9
+ | `name` or `bot` | The character's name. |
10
+ | `context` | A string that appears at the top of the prompt. It usually contains a description of the character's personality and a few example messages. |
11
+ | `greeting` (optional) | The character's opening message. It appears when the character is first loaded or when the history is cleared. |
12
+ | `your_name` or `user` (optional) | Your name. This overwrites what you had previously written in the `Your name` field in the interface. |
13
+
14
+ #### Special tokens
15
+
16
+ The following replacements happen when the prompt is generated, and they apply to the `context` and `greeting` fields:
17
+
18
+ * `{{char}}` and `<BOT>` get replaced with the character's name.
19
+ * `{{user}}` and `<USER>` get replaced with your name.
20
+
21
+ #### How do I add a profile picture for my character?
22
+
23
+ Put an image with the same name as your character's `.yaml` file into the `characters` folder. For example, if your bot is `Character.yaml`, add `Character.jpg` or `Character.png` to the folder.
24
+
25
+ #### Is the chat history truncated in the prompt?
26
+
27
+ Once your prompt reaches the `truncation_length` parameter (2048 by default), old messages will be removed one at a time. The context string will always stay at the top of the prompt and will never get truncated.
28
+
29
+ ## Chat styles
30
+
31
+ Custom chat styles can be defined in the `text-generation-webui/css` folder. Simply create a new file with name starting in `chat_style-` and ending in `.css` and it will automatically appear in the "Chat style" dropdown menu in the interface. Examples:
32
+
33
+ ```
34
+ chat_style-cai-chat.css
35
+ chat_style-TheEncrypted777.css
36
+ chat_style-wpp.css
37
+ ```
38
+
39
+ You should use the same class names as in `chat_style-cai-chat.css` in your custom style.
docs/DeepSpeed.md ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ An alternative way of reducing the GPU memory usage of models is to use the `DeepSpeed ZeRO-3` optimization.
2
+
3
+ With this, I have been able to load a 6b model (GPT-J 6B) with less than 6GB of VRAM. The speed of text generation is very decent and much better than what would be accomplished with `--auto-devices --gpu-memory 6`.
4
+
5
+ As far as I know, DeepSpeed is only available for Linux at the moment.
6
+
7
+ ### How to use it
8
+
9
+ 1. Install DeepSpeed:
10
+
11
+ ```
12
+ conda install -c conda-forge mpi4py mpich
13
+ pip install -U deepspeed
14
+ ```
15
+
16
+ 2. Start the web UI replacing `python` with `deepspeed --num_gpus=1` and adding the `--deepspeed` flag. Example:
17
+
18
+ ```
19
+ deepspeed --num_gpus=1 server.py --deepspeed --chat --model gpt-j-6B
20
+ ```
21
+
22
+ ### Learn more
23
+
24
+ For more information, check out [this comment](https://github.com/oobabooga/text-generation-webui/issues/40#issuecomment-1412038622) by 81300, who came up with the DeepSpeed support in this web UI.
docs/Docker.md ADDED
@@ -0,0 +1,203 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Docker Compose is a way of installing and launching the web UI in an isolated Ubuntu image using only a few commands.
2
+
3
+ In order to create the image as described in the main README, you must have docker compose 2.17 or higher:
4
+
5
+ ```
6
+ ~$ docker compose version
7
+ Docker Compose version v2.17.2
8
+ ```
9
+
10
+ Make sure to also create the necessary symbolic links:
11
+
12
+ ```
13
+ cd text-generation-webui
14
+ ln -s docker/{Dockerfile,docker-compose.yml,.dockerignore} .
15
+ cp docker/.env.example .env
16
+ # Edit .env and set TORCH_CUDA_ARCH_LIST based on your GPU model
17
+ docker compose up --build
18
+ ```
19
+
20
+ # Table of contents
21
+
22
+ * [Docker Compose installation instructions](#docker-compose-installation-instructions)
23
+ * [Repository with additional Docker files](#dedicated-docker-repository)
24
+
25
+ # Docker Compose installation instructions
26
+
27
+ By [@loeken](https://github.com/loeken).
28
+
29
+ - [Ubuntu 22.04](#ubuntu-2204)
30
+ - [0. youtube video](#0-youtube-video)
31
+ - [1. update the drivers](#1-update-the-drivers)
32
+ - [2. reboot](#2-reboot)
33
+ - [3. install docker](#3-install-docker)
34
+ - [4. docker \& container toolkit](#4-docker--container-toolkit)
35
+ - [5. clone the repo](#5-clone-the-repo)
36
+ - [6. prepare models](#6-prepare-models)
37
+ - [7. prepare .env file](#7-prepare-env-file)
38
+ - [8. startup docker container](#8-startup-docker-container)
39
+ - [Manjaro](#manjaro)
40
+ - [update the drivers](#update-the-drivers)
41
+ - [reboot](#reboot)
42
+ - [docker \& container toolkit](#docker--container-toolkit)
43
+ - [continue with ubuntu task](#continue-with-ubuntu-task)
44
+ - [Windows](#windows)
45
+ - [0. youtube video](#0-youtube-video-1)
46
+ - [1. choco package manager](#1-choco-package-manager)
47
+ - [2. install drivers/dependencies](#2-install-driversdependencies)
48
+ - [3. install wsl](#3-install-wsl)
49
+ - [4. reboot](#4-reboot)
50
+ - [5. git clone \&\& startup](#5-git-clone--startup)
51
+ - [6. prepare models](#6-prepare-models-1)
52
+ - [7. startup](#7-startup)
53
+ - [notes](#notes)
54
+
55
+ ## Ubuntu 22.04
56
+
57
+ ### 0. youtube video
58
+ A video walking you through the setup can be found here:
59
+
60
+ [![oobabooga text-generation-webui setup in docker on ubuntu 22.04](https://img.youtube.com/vi/ELkKWYh8qOk/0.jpg)](https://www.youtube.com/watch?v=ELkKWYh8qOk)
61
+
62
+
63
+ ### 1. update the drivers
64
+ in the the “software updater” update drivers to the last version of the prop driver.
65
+
66
+ ### 2. reboot
67
+ to switch using to new driver
68
+
69
+ ### 3. install docker
70
+ ```bash
71
+ sudo apt update
72
+ sudo apt-get install curl
73
+ sudo mkdir -m 0755 -p /etc/apt/keyrings
74
+ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
75
+ echo \
76
+ "deb [arch="$(dpkg --print-architecture)" signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
77
+ "$(. /etc/os-release && echo "$VERSION_CODENAME")" stable" | \
78
+ sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
79
+ sudo apt update
80
+ sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin docker-compose -y
81
+ sudo usermod -aG docker $USER
82
+ newgrp docker
83
+ ```
84
+
85
+ ### 4. docker & container toolkit
86
+ ```bash
87
+ curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
88
+ echo "deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/stable/ubuntu22.04/amd64 /" | \
89
+ sudo tee /etc/apt/sources.list.d/nvidia.list > /dev/null
90
+ sudo apt update
91
+ sudo apt install nvidia-docker2 nvidia-container-runtime -y
92
+ sudo systemctl restart docker
93
+ ```
94
+
95
+ ### 5. clone the repo
96
+ ```
97
+ git clone https://github.com/oobabooga/text-generation-webui
98
+ cd text-generation-webui
99
+ ```
100
+
101
+ ### 6. prepare models
102
+ download and place the models inside the models folder. tested with:
103
+
104
+ 4bit
105
+ https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483891617
106
+ https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483941105
107
+
108
+ 8bit:
109
+ https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1484235789
110
+
111
+ ### 7. prepare .env file
112
+ edit .env values to your needs.
113
+ ```bash
114
+ cp .env.example .env
115
+ nano .env
116
+ ```
117
+
118
+ ### 8. startup docker container
119
+ ```bash
120
+ docker compose up --build
121
+ ```
122
+
123
+ ## Manjaro
124
+ manjaro/arch is similar to ubuntu just the dependency installation is more convenient
125
+
126
+ ### update the drivers
127
+ ```bash
128
+ sudo mhwd -a pci nonfree 0300
129
+ ```
130
+ ### reboot
131
+ ```bash
132
+ reboot
133
+ ```
134
+ ### docker & container toolkit
135
+ ```bash
136
+ yay -S docker docker-compose buildkit gcc nvidia-docker
137
+ sudo usermod -aG docker $USER
138
+ newgrp docker
139
+ sudo systemctl restart docker # required by nvidia-container-runtime
140
+ ```
141
+
142
+ ### continue with ubuntu task
143
+ continue at [5. clone the repo](#5-clone-the-repo)
144
+
145
+ ## Windows
146
+ ### 0. youtube video
147
+ A video walking you through the setup can be found here:
148
+ [![oobabooga text-generation-webui setup in docker on windows 11](https://img.youtube.com/vi/ejH4w5b5kFQ/0.jpg)](https://www.youtube.com/watch?v=ejH4w5b5kFQ)
149
+
150
+ ### 1. choco package manager
151
+ install package manager (https://chocolatey.org/ )
152
+ ```
153
+ Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
154
+ ```
155
+
156
+ ### 2. install drivers/dependencies
157
+ ```
158
+ choco install nvidia-display-driver cuda git docker-desktop
159
+ ```
160
+
161
+ ### 3. install wsl
162
+ wsl --install
163
+
164
+ ### 4. reboot
165
+ after reboot enter username/password in wsl
166
+
167
+ ### 5. git clone && startup
168
+ clone the repo and edit .env values to your needs.
169
+ ```
170
+ cd Desktop
171
+ git clone https://github.com/oobabooga/text-generation-webui
172
+ cd text-generation-webui
173
+ COPY .env.example .env
174
+ notepad .env
175
+ ```
176
+
177
+ ### 6. prepare models
178
+ download and place the models inside the models folder. tested with:
179
+
180
+ 4bit https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483891617 https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483941105
181
+
182
+ 8bit: https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1484235789
183
+
184
+ ### 7. startup
185
+ ```
186
+ docker compose up
187
+ ```
188
+
189
+ ## notes
190
+
191
+ on older ubuntus you can manually install the docker compose plugin like this:
192
+ ```
193
+ DOCKER_CONFIG=${DOCKER_CONFIG:-$HOME/.docker}
194
+ mkdir -p $DOCKER_CONFIG/cli-plugins
195
+ curl -SL https://github.com/docker/compose/releases/download/v2.17.2/docker-compose-linux-x86_64 -o $DOCKER_CONFIG/cli-plugins/docker-compose
196
+ chmod +x $DOCKER_CONFIG/cli-plugins/docker-compose
197
+ export PATH="$HOME/.docker/cli-plugins:$PATH"
198
+ ```
199
+
200
+ # Dedicated docker repository
201
+
202
+ An external repository maintains a docker wrapper for this project as well as several pre-configured 'one-click' `docker compose` variants (e.g., updated branches of GPTQ). It can be found at: [Atinoda/text-generation-webui-docker](https://github.com/Atinoda/text-generation-webui-docker).
203
+
docs/ExLlama.md ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # ExLlama
2
+
3
+ ### About
4
+
5
+ ExLlama is an extremely optimized GPTQ backend for LLaMA models. It features much lower VRAM usage and much higher speeds due to not relying on unoptimized transformers code.
6
+
7
+ ### Usage
8
+
9
+ Configure text-generation-webui to use exllama via the UI or command line:
10
+ - In the "Model" tab, set "Loader" to "exllama"
11
+ - Specify `--loader exllama` on the command line
12
+
13
+ ### Manual setup
14
+
15
+ No additional installation steps are necessary since an exllama package is already included in the requirements.txt. If this package fails to install for some reason, you can install it manually by cloning the original repository into your `repositories/` folder:
16
+
17
+ ```
18
+ mkdir repositories
19
+ cd repositories
20
+ git clone https://github.com/turboderp/exllama
21
+ ```
22
+
docs/Extensions.md ADDED
@@ -0,0 +1,244 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Extensions
2
+
3
+ Extensions are defined by files named `script.py` inside subfolders of `text-generation-webui/extensions`. They are loaded at startup if the folder name is specified after the `--extensions` flag.
4
+
5
+ For instance, `extensions/silero_tts/script.py` gets loaded with `python server.py --extensions silero_tts`.
6
+
7
+ ## [text-generation-webui-extensions](https://github.com/oobabooga/text-generation-webui-extensions)
8
+
9
+ The repository above contains a directory of user extensions.
10
+
11
+ If you create an extension, you are welcome to host it in a GitHub repository and submit a PR adding it to the list.
12
+
13
+ ## Built-in extensions
14
+
15
+ |Extension|Description|
16
+ |---------|-----------|
17
+ |[api](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/api)| Creates an API with two endpoints, one for streaming at `/api/v1/stream` port 5005 and another for blocking at `/api/v1/generate` port 5000. This is the main API for the webui. |
18
+ |[openai](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/openai)| Creates an API that mimics the OpenAI API and can be used as a drop-in replacement. |
19
+ |[multimodal](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal) | Adds multimodality support (text+images). For a detailed description see [README.md](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal/README.md) in the extension directory. |
20
+ |[google_translate](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/google_translate)| Automatically translates inputs and outputs using Google Translate.|
21
+ |[silero_tts](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/silero_tts)| Text-to-speech extension using [Silero](https://github.com/snakers4/silero-models). When used in chat mode, responses are replaced with an audio widget. |
22
+ |[elevenlabs_tts](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/elevenlabs_tts)| Text-to-speech extension using the [ElevenLabs](https://beta.elevenlabs.io/) API. You need an API key to use it. |
23
+ |[whisper_stt](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/whisper_stt)| Allows you to enter your inputs in chat mode using your microphone. |
24
+ |[sd_api_pictures](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/sd_api_pictures)| Allows you to request pictures from the bot in chat mode, which will be generated using the AUTOMATIC1111 Stable Diffusion API. See examples [here](https://github.com/oobabooga/text-generation-webui/pull/309). |
25
+ |[character_bias](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/character_bias)| Just a very simple example that adds a hidden string at the beginning of the bot's reply in chat mode. |
26
+ |[send_pictures](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/send_pictures/)| Creates an image upload field that can be used to send images to the bot in chat mode. Captions are automatically generated using BLIP. |
27
+ |[gallery](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/gallery/)| Creates a gallery with the chat characters and their pictures. |
28
+ |[superbooga](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/superbooga)| An extension that uses ChromaDB to create an arbitrarily large pseudocontext, taking as input text files, URLs, or pasted text. Based on https://github.com/kaiokendev/superbig. |
29
+ |[ngrok](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/ngrok)| Allows you to access the web UI remotely using the ngrok reverse tunnel service (free). It's an alternative to the built-in Gradio `--share` feature. |
30
+ |[perplexity_colors](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/perplexity_colors)| Colors each token in the output text by its associated probability, as derived from the model logits. |
31
+
32
+ ## How to write an extension
33
+
34
+ The extensions framework is based on special functions and variables that you can define in `script.py`. The functions are the following:
35
+
36
+ | Function | Description |
37
+ |-------------|-------------|
38
+ | `def setup()` | Is executed when the extension gets imported. |
39
+ | `def ui()` | Creates custom gradio elements when the UI is launched. |
40
+ | `def custom_css()` | Returns custom CSS as a string. It is applied whenever the web UI is loaded. |
41
+ | `def custom_js()` | Same as above but for javascript. |
42
+ | `def input_modifier(string, state)` | Modifies the input string before it enters the model. In chat mode, it is applied to the user message. Otherwise, it is applied to the entire prompt. |
43
+ | `def output_modifier(string, state)` | Modifies the output string before it is presented in the UI. In chat mode, it is applied to the bot's reply. Otherwise, it is applied to the entire output. |
44
+ | `def chat_input_modifier(text, visible_text, state)` | Modifies both the visible and internal inputs in chat mode. Can be used to hijack the chat input with custom content. |
45
+ | `def bot_prefix_modifier(string, state)` | Applied in chat mode to the prefix for the bot's reply. |
46
+ | `def state_modifier(state)` | Modifies the dictionary containing the UI input parameters before it is used by the text generation functions. |
47
+ | `def history_modifier(history)` | Modifies the chat history before the text generation in chat mode begins. |
48
+ | `def custom_generate_reply(...)` | Overrides the main text generation function. |
49
+ | `def custom_generate_chat_prompt(...)` | Overrides the prompt generator in chat mode. |
50
+ | `def tokenizer_modifier(state, prompt, input_ids, input_embeds)` | Modifies the `input_ids`/`input_embeds` fed to the model. Should return `prompt`, `input_ids`, `input_embeds`. See the `multimodal` extension for an example. |
51
+ | `def custom_tokenized_length(prompt)` | Used in conjunction with `tokenizer_modifier`, returns the length in tokens of `prompt`. See the `multimodal` extension for an example. |
52
+
53
+ Additionally, you can define a special `params` dictionary. In it, the `display_name` key is used to define the displayed name of the extension in the UI, and the `is_tab` key is used to define whether the extension should appear in a new tab. By default, extensions appear at the bottom of the "Text generation" tab.
54
+
55
+ Example:
56
+
57
+ ```python
58
+ params = {
59
+ "display_name": "Google Translate",
60
+ "is_tab": True,
61
+ }
62
+ ```
63
+
64
+ The `params` dict may also contain variables that you want to be customizable through a `settings.yaml` file. For instance, assuming the extension is in `extensions/google_translate`, the variable `language string` in
65
+
66
+ ```python
67
+ params = {
68
+ "display_name": "Google Translate",
69
+ "is_tab": True,
70
+ "language string": "jp"
71
+ }
72
+ ```
73
+
74
+ can be customized by adding a key called `google_translate-language string` to `settings.yaml`:
75
+
76
+ ```python
77
+ google_translate-language string: 'fr'
78
+ ```
79
+
80
+ That is, the syntax for the key is `extension_name-variable_name`.
81
+
82
+ ## Using multiple extensions at the same time
83
+
84
+ You can activate more than one extension at a time by providing their names separated by spaces after `--extensions`. The input, output, and bot prefix modifiers will be applied in the specified order.
85
+
86
+ Example:
87
+
88
+ ```
89
+ python server.py --extensions enthusiasm translate # First apply enthusiasm, then translate
90
+ python server.py --extensions translate enthusiasm # First apply translate, then enthusiasm
91
+ ```
92
+
93
+ Do note, that for:
94
+ - `custom_generate_chat_prompt`
95
+ - `custom_generate_reply`
96
+ - `custom_tokenized_length`
97
+
98
+ only the first declaration encountered will be used and the rest will be ignored.
99
+
100
+ ## A full example
101
+
102
+ The source code below can be found at [extensions/example/script.py](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/example/script.py).
103
+
104
+ ```python
105
+ """
106
+ An example of extension. It does nothing, but you can add transformations
107
+ before the return statements to customize the webui behavior.
108
+
109
+ Starting from history_modifier and ending in output_modifier, the
110
+ functions are declared in the same order that they are called at
111
+ generation time.
112
+ """
113
+
114
+ import gradio as gr
115
+ import torch
116
+ from transformers import LogitsProcessor
117
+
118
+ from modules import chat, shared
119
+ from modules.text_generation import (
120
+ decode,
121
+ encode,
122
+ generate_reply,
123
+ )
124
+
125
+ params = {
126
+ "display_name": "Example Extension",
127
+ "is_tab": False,
128
+ }
129
+
130
+ class MyLogits(LogitsProcessor):
131
+ """
132
+ Manipulates the probabilities for the next token before it gets sampled.
133
+ Used in the logits_processor_modifier function below.
134
+ """
135
+ def __init__(self):
136
+ pass
137
+
138
+ def __call__(self, input_ids, scores):
139
+ # probs = torch.softmax(scores, dim=-1, dtype=torch.float)
140
+ # probs[0] /= probs[0].sum()
141
+ # scores = torch.log(probs / (1 - probs))
142
+ return scores
143
+
144
+ def history_modifier(history):
145
+ """
146
+ Modifies the chat history.
147
+ Only used in chat mode.
148
+ """
149
+ return history
150
+
151
+ def state_modifier(state):
152
+ """
153
+ Modifies the state variable, which is a dictionary containing the input
154
+ values in the UI like sliders and checkboxes.
155
+ """
156
+ return state
157
+
158
+ def chat_input_modifier(text, visible_text, state):
159
+ """
160
+ Modifies the user input string in chat mode (visible_text).
161
+ You can also modify the internal representation of the user
162
+ input (text) to change how it will appear in the prompt.
163
+ """
164
+ return text, visible_text
165
+
166
+ def input_modifier(string, state):
167
+ """
168
+ In default/notebook modes, modifies the whole prompt.
169
+
170
+ In chat mode, it is the same as chat_input_modifier but only applied
171
+ to "text", here called "string", and not to "visible_text".
172
+ """
173
+ return string
174
+
175
+ def bot_prefix_modifier(string, state):
176
+ """
177
+ Modifies the prefix for the next bot reply in chat mode.
178
+ By default, the prefix will be something like "Bot Name:".
179
+ """
180
+ return string
181
+
182
+ def tokenizer_modifier(state, prompt, input_ids, input_embeds):
183
+ """
184
+ Modifies the input ids and embeds.
185
+ Used by the multimodal extension to put image embeddings in the prompt.
186
+ Only used by loaders that use the transformers library for sampling.
187
+ """
188
+ return prompt, input_ids, input_embeds
189
+
190
+ def logits_processor_modifier(processor_list, input_ids):
191
+ """
192
+ Adds logits processors to the list, allowing you to access and modify
193
+ the next token probabilities.
194
+ Only used by loaders that use the transformers library for sampling.
195
+ """
196
+ processor_list.append(MyLogits())
197
+ return processor_list
198
+
199
+ def output_modifier(string, state):
200
+ """
201
+ Modifies the LLM output before it gets presented.
202
+
203
+ In chat mode, the modified version goes into history['visible'],
204
+ and the original version goes into history['internal'].
205
+ """
206
+ return string
207
+
208
+ def custom_generate_chat_prompt(user_input, state, **kwargs):
209
+ """
210
+ Replaces the function that generates the prompt from the chat history.
211
+ Only used in chat mode.
212
+ """
213
+ result = chat.generate_chat_prompt(user_input, state, **kwargs)
214
+ return result
215
+
216
+ def custom_css():
217
+ """
218
+ Returns a CSS string that gets appended to the CSS for the webui.
219
+ """
220
+ return ''
221
+
222
+ def custom_js():
223
+ """
224
+ Returns a javascript string that gets appended to the javascript
225
+ for the webui.
226
+ """
227
+ return ''
228
+
229
+ def setup():
230
+ """
231
+ Gets executed only once, when the extension is imported.
232
+ """
233
+ pass
234
+
235
+ def ui():
236
+ """
237
+ Gets executed when the UI is drawn. Custom gradio elements and
238
+ their corresponding event handlers should be defined here.
239
+
240
+ To learn about gradio components, check out the docs:
241
+ https://gradio.app/docs/
242
+ """
243
+ pass
244
+ ```
docs/GPTQ-models-(4-bit-mode).md ADDED
@@ -0,0 +1,187 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ GPTQ is a clever quantization algorithm that lightly reoptimizes the weights during quantization so that the accuracy loss is compensated relative to a round-to-nearest quantization. See the paper for more details: https://arxiv.org/abs/2210.17323
2
+
3
+ 4-bit GPTQ models reduce VRAM usage by about 75%. So LLaMA-7B fits into a 6GB GPU, and LLaMA-30B fits into a 24GB GPU.
4
+
5
+ ## Overview
6
+
7
+ There are two ways of loading GPTQ models in the web UI at the moment:
8
+
9
+ * Using AutoGPTQ:
10
+ * supports more models
11
+ * standardized (no need to guess any parameter)
12
+ * is a proper Python library
13
+ * ~no wheels are presently available so it requires manual compilation~
14
+ * supports loading both triton and cuda models
15
+
16
+ * Using GPTQ-for-LLaMa directly:
17
+ * faster CPU offloading
18
+ * faster multi-GPU inference
19
+ * supports loading LoRAs using a monkey patch
20
+ * requires you to manually figure out the wbits/groupsize/model_type parameters for the model to be able to load it
21
+ * supports either only cuda or only triton depending on the branch
22
+
23
+ For creating new quantizations, I recommend using AutoGPTQ: https://github.com/PanQiWei/AutoGPTQ
24
+
25
+ ## AutoGPTQ
26
+
27
+ ### Installation
28
+
29
+ No additional steps are necessary as AutoGPTQ is already in the `requirements.txt` for the webui. If you still want or need to install it manually for whatever reason, these are the commands:
30
+
31
+ ```
32
+ conda activate textgen
33
+ git clone https://github.com/PanQiWei/AutoGPTQ.git && cd AutoGPTQ
34
+ pip install .
35
+ ```
36
+
37
+ The last command requires `nvcc` to be installed (see the [instructions above](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md#step-1-install-nvcc)).
38
+
39
+ ### Usage
40
+
41
+ When you quantize a model using AutoGPTQ, a folder containing a filed called `quantize_config.json` will be generated. Place that folder inside your `models/` folder and load it with the `--autogptq` flag:
42
+
43
+ ```
44
+ python server.py --autogptq --model model_name
45
+ ```
46
+
47
+ Alternatively, check the `autogptq` box in the "Model" tab of the UI before loading the model.
48
+
49
+ ### Offloading
50
+
51
+ In order to do CPU offloading or multi-gpu inference with AutoGPTQ, use the `--gpu-memory` flag. It is currently somewhat slower than offloading with the `--pre_layer` option in GPTQ-for-LLaMA.
52
+
53
+ For CPU offloading:
54
+
55
+ ```
56
+ python server.py --autogptq --gpu-memory 3000MiB --model model_name
57
+ ```
58
+
59
+ For multi-GPU inference:
60
+
61
+ ```
62
+ python server.py --autogptq --gpu-memory 3000MiB 6000MiB --model model_name
63
+ ```
64
+
65
+ ### Using LoRAs with AutoGPTQ
66
+
67
+ Works fine for a single LoRA.
68
+
69
+ ## GPTQ-for-LLaMa
70
+
71
+ GPTQ-for-LLaMa is the original adaptation of GPTQ for the LLaMA model. It was made possible by [@qwopqwop200](https://github.com/qwopqwop200/GPTQ-for-LLaMa): https://github.com/qwopqwop200/GPTQ-for-LLaMa
72
+
73
+ A Python package containing both major CUDA versions of GPTQ-for-LLaMa is used to simplify installation and compatibility: https://github.com/jllllll/GPTQ-for-LLaMa-CUDA
74
+
75
+ ### Precompiled wheels
76
+
77
+ Kindly provided by our friend jllllll: https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases
78
+
79
+ Wheels are included in requirements.txt and are installed with the webui on supported systems.
80
+
81
+ ### Manual installation
82
+
83
+ #### Step 1: install nvcc
84
+
85
+ ```
86
+ conda activate textgen
87
+ conda install cuda -c nvidia/label/cuda-11.7.1
88
+ ```
89
+
90
+ The command above takes some 10 minutes to run and shows no progress bar or updates along the way.
91
+
92
+ You are also going to need to have a C++ compiler installed. On Linux, `sudo apt install build-essential` or equivalent is enough. On Windows, Visual Studio or Visual Studio Build Tools is required.
93
+
94
+ If you're using an older version of CUDA toolkit (e.g. 11.7) but the latest version of `gcc` and `g++` (12.0+) on Linux, you should downgrade with: `conda install -c conda-forge gxx==11.3.0`. Kernel compilation will fail otherwise.
95
+
96
+ #### Step 2: compile the CUDA extensions
97
+
98
+ ```
99
+ python -m pip install git+https://github.com/jllllll/GPTQ-for-LLaMa-CUDA -v
100
+ ```
101
+
102
+ ### Getting pre-converted LLaMA weights
103
+
104
+ * Direct download (recommended):
105
+
106
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-7B-4bit-128g
107
+
108
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-13B-4bit-128g
109
+
110
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-30B-4bit-128g
111
+
112
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-65B-4bit-128g
113
+
114
+ These models were converted with `desc_act=True`. They work just fine with ExLlama. For AutoGPTQ, they will only work on Linux with the `triton` option checked.
115
+
116
+ * Torrent:
117
+
118
+ https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483891617
119
+
120
+ https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483941105
121
+
122
+ These models were converted with `desc_act=False`. As such, they are less accurate, but they work with AutoGPTQ on Windows. The `128g` versions are better from 13b upwards, and worse for 7b. The tokenizer files in the torrents are outdated, in particular the files called `tokenizer_config.json` and `special_tokens_map.json`. Here you can find those files: https://huggingface.co/oobabooga/llama-tokenizer
123
+
124
+ ### Starting the web UI:
125
+
126
+ Use the `--gptq-for-llama` flag.
127
+
128
+ For the models converted without `group-size`:
129
+
130
+ ```
131
+ python server.py --model llama-7b-4bit --gptq-for-llama
132
+ ```
133
+
134
+ For the models converted with `group-size`:
135
+
136
+ ```
137
+ python server.py --model llama-13b-4bit-128g --gptq-for-llama --wbits 4 --groupsize 128
138
+ ```
139
+
140
+ The command-line flags `--wbits` and `--groupsize` are automatically detected based on the folder names in many cases.
141
+
142
+ ### CPU offloading
143
+
144
+ It is possible to offload part of the layers of the 4-bit model to the CPU with the `--pre_layer` flag. The higher the number after `--pre_layer`, the more layers will be allocated to the GPU.
145
+
146
+ With this command, I can run llama-7b with 4GB VRAM:
147
+
148
+ ```
149
+ python server.py --model llama-7b-4bit --pre_layer 20
150
+ ```
151
+
152
+ This is the performance:
153
+
154
+ ```
155
+ Output generated in 123.79 seconds (1.61 tokens/s, 199 tokens)
156
+ ```
157
+
158
+ You can also use multiple GPUs with `pre_layer` if using the oobabooga fork of GPTQ, eg `--pre_layer 30 60` will load a LLaMA-30B model half onto your first GPU and half onto your second, or `--pre_layer 20 40` will load 20 layers onto GPU-0, 20 layers onto GPU-1, and 20 layers offloaded to CPU.
159
+
160
+ ### Using LoRAs with GPTQ-for-LLaMa
161
+
162
+ This requires using a monkey patch that is supported by this web UI: https://github.com/johnsmith0031/alpaca_lora_4bit
163
+
164
+ To use it:
165
+
166
+ 1. Clone `johnsmith0031/alpaca_lora_4bit` into the repositories folder:
167
+
168
+ ```
169
+ cd text-generation-webui/repositories
170
+ git clone https://github.com/johnsmith0031/alpaca_lora_4bit
171
+ ```
172
+
173
+ ⚠️ I have tested it with the following commit specifically: `2f704b93c961bf202937b10aac9322b092afdce0`
174
+
175
+ 2. Install https://github.com/sterlind/GPTQ-for-LLaMa with this command:
176
+
177
+ ```
178
+ pip install git+https://github.com/sterlind/GPTQ-for-LLaMa.git@lora_4bit
179
+ ```
180
+
181
+ 3. Start the UI with the `--monkey-patch` flag:
182
+
183
+ ```
184
+ python server.py --model llama-7b-4bit-128g --listen --lora tloen_alpaca-lora-7b --monkey-patch
185
+ ```
186
+
187
+
docs/LLaMA-model.md ADDED
@@ -0,0 +1,56 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ LLaMA is a Large Language Model developed by Meta AI.
2
+
3
+ It was trained on more tokens than previous models. The result is that the smallest version with 7 billion parameters has similar performance to GPT-3 with 175 billion parameters.
4
+
5
+ This guide will cover usage through the official `transformers` implementation. For 4-bit mode, head over to [GPTQ models (4 bit mode)
6
+ ](GPTQ-models-(4-bit-mode).md).
7
+
8
+ ## Getting the weights
9
+
10
+ ### Option 1: pre-converted weights
11
+
12
+ * Direct download (recommended):
13
+
14
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-7B-HF
15
+
16
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-13B-HF
17
+
18
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-30B-HF
19
+
20
+ https://huggingface.co/Neko-Institute-of-Science/LLaMA-65B-HF
21
+
22
+ * Torrent:
23
+
24
+ https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1484235789
25
+
26
+ The tokenizer files in the torrent above are outdated, in particular the files called `tokenizer_config.json` and `special_tokens_map.json`. Here you can find those files: https://huggingface.co/oobabooga/llama-tokenizer
27
+
28
+ ### Option 2: convert the weights yourself
29
+
30
+ 1. Install the `protobuf` library:
31
+
32
+ ```
33
+ pip install protobuf==3.20.1
34
+ ```
35
+
36
+ 2. Use the script below to convert the model in `.pth` format that you, a fellow academic, downloaded using Meta's official link.
37
+
38
+ If you have `transformers` installed in place:
39
+
40
+ ```
41
+ python -m transformers.models.llama.convert_llama_weights_to_hf --input_dir /path/to/LLaMA --model_size 7B --output_dir /tmp/outputs/llama-7b
42
+ ```
43
+
44
+ Otherwise download [convert_llama_weights_to_hf.py](https://github.com/huggingface/transformers/blob/main/src/transformers/models/llama/convert_llama_weights_to_hf.py) first and run:
45
+
46
+ ```
47
+ python convert_llama_weights_to_hf.py --input_dir /path/to/LLaMA --model_size 7B --output_dir /tmp/outputs/llama-7b
48
+ ```
49
+
50
+ 3. Move the `llama-7b` folder inside your `text-generation-webui/models` folder.
51
+
52
+ ## Starting the web UI
53
+
54
+ ```python
55
+ python server.py --model llama-7b
56
+ ```
docs/LLaMA-v2-model.md ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # LLaMA-v2
2
+
3
+ To convert LLaMA-v2 from the `.pth` format provided by Meta to transformers format, follow the steps below:
4
+
5
+ 1) `cd` into your `llama` folder (the one containing `download.sh` and the models that you downloaded):
6
+
7
+ ```
8
+ cd llama
9
+ ```
10
+
11
+ 2) Clone the transformers library:
12
+
13
+ ```
14
+ git clone 'https://github.com/huggingface/transformers'
15
+
16
+ ```
17
+
18
+ 3) Create symbolic links from the downloaded folders to names that the conversion script can recognize:
19
+
20
+ ```
21
+ ln -s llama-2-7b 7B
22
+ ln -s llama-2-13b 13B
23
+ ```
24
+
25
+ 4) Do the conversions:
26
+
27
+ ```
28
+ mkdir llama-2-7b-hf llama-2-13b-hf
29
+ python ./transformers/src/transformers/models/llama/convert_llama_weights_to_hf.py --input_dir . --model_size 7B --output_dir llama-2-7b-hf --safe_serialization true
30
+ python ./transformers/src/transformers/models/llama/convert_llama_weights_to_hf.py --input_dir . --model_size 13B --output_dir llama-2-13b-hf --safe_serialization true
31
+ ```
32
+
33
+ 5) Move the output folders inside `text-generation-webui/models`
34
+
35
+ 6) Have fun
docs/LoRA.md ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # LoRA
2
+
3
+ LoRA (Low-Rank Adaptation) is an extremely powerful method for customizing a base model by training only a small number of parameters. They can be attached to models at runtime.
4
+
5
+ For instance, a 50mb LoRA can teach LLaMA an entire new language, a given writing style, or give it instruction-following or chat abilities.
6
+
7
+ This is the current state of LoRA integration in the web UI:
8
+
9
+ |Loader | Status |
10
+ |--------|------|
11
+ | Transformers | Full support in 16-bit, `--load-in-8bit`, `--load-in-4bit`, and CPU modes. |
12
+ | ExLlama | Single LoRA support. Fast to remove the LoRA afterwards. |
13
+ | AutoGPTQ | Single LoRA support. Removing the LoRA requires reloading the entire model.|
14
+ | GPTQ-for-LLaMa | Full support with the [monkey patch](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md#using-loras-with-gptq-for-llama). |
15
+
16
+ ## Downloading a LoRA
17
+
18
+ The download script can be used. For instance:
19
+
20
+ ```
21
+ python download-model.py tloen/alpaca-lora-7b
22
+ ```
23
+
24
+ The files will be saved to `loras/tloen_alpaca-lora-7b`.
25
+
26
+ ## Using the LoRA
27
+
28
+ The `--lora` command-line flag can be used. Examples:
29
+
30
+ ```
31
+ python server.py --model llama-7b-hf --lora tloen_alpaca-lora-7b
32
+ python server.py --model llama-7b-hf --lora tloen_alpaca-lora-7b --load-in-8bit
33
+ python server.py --model llama-7b-hf --lora tloen_alpaca-lora-7b --load-in-4bit
34
+ python server.py --model llama-7b-hf --lora tloen_alpaca-lora-7b --cpu
35
+ ```
36
+
37
+ Instead of using the `--lora` command-line flag, you can also select the LoRA in the "Parameters" tab of the interface.
38
+
39
+ ## Prompt
40
+ For the Alpaca LoRA in particular, the prompt must be formatted like this:
41
+
42
+ ```
43
+ Below is an instruction that describes a task. Write a response that appropriately completes the request.
44
+ ### Instruction:
45
+ Write a Python script that generates text using the transformers library.
46
+ ### Response:
47
+ ```
48
+
49
+ Sample output:
50
+
51
+ ```
52
+ Below is an instruction that describes a task. Write a response that appropriately completes the request.
53
+ ### Instruction:
54
+ Write a Python script that generates text using the transformers library.
55
+ ### Response:
56
+
57
+ import transformers
58
+ from transformers import AutoTokenizer, AutoModelForCausalLM
59
+ tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
60
+ model = AutoModelForCausalLM.from_pretrained("bert-base-uncased")
61
+ texts = ["Hello world", "How are you"]
62
+ for sentence in texts:
63
+ sentence = tokenizer(sentence)
64
+ print(f"Generated {len(sentence)} tokens from '{sentence}'")
65
+ output = model(sentences=sentence).predict()
66
+ print(f"Predicted {len(output)} tokens for '{sentence}':\n{output}")
67
+ ```
68
+
69
+ ## Training a LoRA
70
+
71
+ You can train your own LoRAs from the `Training` tab. See [Training LoRAs](Training-LoRAs.md) for details.
docs/Low-VRAM-guide.md ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ If you GPU is not large enough to fit a 16-bit model, try these in the following order:
2
+
3
+ ### Load the model in 8-bit mode
4
+
5
+ ```
6
+ python server.py --load-in-8bit
7
+ ```
8
+
9
+ ### Load the model in 4-bit mode
10
+
11
+ ```
12
+ python server.py --load-in-4bit
13
+ ```
14
+
15
+ ### Split the model across your GPU and CPU
16
+
17
+ ```
18
+ python server.py --auto-devices
19
+ ```
20
+
21
+ If you can load the model with this command but it runs out of memory when you try to generate text, try increasingly limiting the amount of memory allocated to the GPU until the error stops happening:
22
+
23
+ ```
24
+ python server.py --auto-devices --gpu-memory 10
25
+ python server.py --auto-devices --gpu-memory 9
26
+ python server.py --auto-devices --gpu-memory 8
27
+ ...
28
+ ```
29
+
30
+ where the number is in GiB.
31
+
32
+ For finer control, you can also specify the unit in MiB explicitly:
33
+
34
+ ```
35
+ python server.py --auto-devices --gpu-memory 8722MiB
36
+ python server.py --auto-devices --gpu-memory 4725MiB
37
+ python server.py --auto-devices --gpu-memory 3500MiB
38
+ ...
39
+ ```
40
+
41
+ ### Send layers to a disk cache
42
+
43
+ As a desperate last measure, you can split the model across your GPU, CPU, and disk:
44
+
45
+ ```
46
+ python server.py --auto-devices --disk
47
+ ```
48
+
49
+ With this, I am able to load a 30b model into my RTX 3090, but it takes 10 seconds to generate 1 word.
50
+
51
+ ### DeepSpeed (experimental)
52
+
53
+ An experimental alternative to all of the above is to use DeepSpeed: [guide](DeepSpeed.md).
docs/README.md ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # text-generation-webui documentation
2
+
3
+ ## Table of contents
4
+
5
+ * [Audio Notification](Audio-Notification.md)
6
+ * [Chat mode](Chat-mode.md)
7
+ * [DeepSpeed](DeepSpeed.md)
8
+ * [Docker](Docker.md)
9
+ * [ExLlama](ExLlama.md)
10
+ * [Extensions](Extensions.md)
11
+ * [GPTQ models (4 bit mode)](GPTQ-models-(4-bit-mode).md)
12
+ * [LLaMA model](LLaMA-model.md)
13
+ * [llama.cpp](llama.cpp.md)
14
+ * [LoRA](LoRA.md)
15
+ * [Low VRAM guide](Low-VRAM-guide.md)
16
+ * [RWKV model](RWKV-model.md)
17
+ * [Spell book](Spell-book.md)
18
+ * [System requirements](System-requirements.md)
19
+ * [Training LoRAs](Training-LoRAs.md)
20
+ * [Windows installation guide](Windows-installation-guide.md)
21
+ * [WSL installation guide](WSL-installation-guide.md)
docs/RWKV-model.md ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ > RWKV: RNN with Transformer-level LLM Performance
2
+ >
3
+ > It combines the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding (using the final hidden state).
4
+
5
+ https://github.com/BlinkDL/RWKV-LM
6
+
7
+ https://github.com/BlinkDL/ChatRWKV
8
+
9
+ ## Using RWKV in the web UI
10
+
11
+ ### Hugging Face weights
12
+
13
+ Simply download the weights from https://huggingface.co/RWKV and load them as you would for any other model.
14
+
15
+ There is a bug in transformers==4.29.2 that prevents RWKV from being loaded in 8-bit mode. You can install the dev branch to solve this bug: `pip install git+https://github.com/huggingface/transformers`
16
+
17
+ ### Original .pth weights
18
+
19
+ The instructions below are from before RWKV was supported in transformers, and they are kept for legacy purposes. The old implementation is possibly faster, but it lacks the full range of samplers that the transformers library offers.
20
+
21
+ #### 0. Install the RWKV library
22
+
23
+ ```
24
+ pip install rwkv
25
+ ```
26
+
27
+ `0.7.3` was the last version that I tested. If you experience any issues, try ```pip install rwkv==0.7.3```.
28
+
29
+ #### 1. Download the model
30
+
31
+ It is available in different sizes:
32
+
33
+ * https://huggingface.co/BlinkDL/rwkv-4-pile-3b/
34
+ * https://huggingface.co/BlinkDL/rwkv-4-pile-7b/
35
+ * https://huggingface.co/BlinkDL/rwkv-4-pile-14b/
36
+
37
+ There are also older releases with smaller sizes like:
38
+
39
+ * https://huggingface.co/BlinkDL/rwkv-4-pile-169m/resolve/main/RWKV-4-Pile-169M-20220807-8023.pth
40
+
41
+ Download the chosen `.pth` and put it directly in the `models` folder.
42
+
43
+ #### 2. Download the tokenizer
44
+
45
+ [20B_tokenizer.json](https://raw.githubusercontent.com/BlinkDL/ChatRWKV/main/v2/20B_tokenizer.json)
46
+
47
+ Also put it directly in the `models` folder. Make sure to not rename it. It should be called `20B_tokenizer.json`.
48
+
49
+ #### 3. Launch the web UI
50
+
51
+ No additional steps are required. Just launch it as you would with any other model.
52
+
53
+ ```
54
+ python server.py --listen --no-stream --model RWKV-4-Pile-169M-20220807-8023.pth
55
+ ```
56
+
57
+ #### Setting a custom strategy
58
+
59
+ It is possible to have very fine control over the offloading and precision for the model with the `--rwkv-strategy` flag. Possible values include:
60
+
61
+ ```
62
+ "cpu fp32" # CPU mode
63
+ "cuda fp16" # GPU mode with float16 precision
64
+ "cuda fp16 *30 -> cpu fp32" # GPU+CPU offloading. The higher the number after *, the higher the GPU allocation.
65
+ "cuda fp16i8" # GPU mode with 8-bit precision
66
+ ```
67
+
68
+ See the README for the PyPl package for more details: https://pypi.org/project/rwkv/
69
+
70
+ #### Compiling the CUDA kernel
71
+
72
+ You can compile the CUDA kernel for the model with `--rwkv-cuda-on`. This should improve the performance a lot but I haven't been able to get it to work yet.
docs/Spell-book.md ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You have now entered a hidden corner of the internet.
2
+
3
+ A confusing yet intriguing realm of paradoxes and contradictions.
4
+
5
+ A place where you will find out that what you thought you knew, you in fact didn't know, and what you didn't know was in front of you all along.
6
+
7
+ ![](https://i.pinimg.com/originals/6e/e2/7b/6ee27bad351d3aca470d80f1033ba9c6.jpg)
8
+
9
+ *In other words, here I will document little-known facts about this web UI that I could not find another place for in the wiki.*
10
+
11
+ #### You can train LoRAs in CPU mode
12
+
13
+ Load the web UI with
14
+
15
+ ```
16
+ python server.py --cpu
17
+ ```
18
+
19
+ and start training the LoRA from the training tab as usual.
20
+
21
+ #### 8-bit mode works with CPU offloading
22
+
23
+ ```
24
+ python server.py --load-in-8bit --gpu-memory 4000MiB
25
+ ```
26
+
27
+ #### `--pre_layer`, and not `--gpu-memory`, is the right way to do CPU offloading with 4-bit models
28
+
29
+ ```
30
+ python server.py --wbits 4 --groupsize 128 --pre_layer 20
31
+ ```
32
+
33
+ #### Models can be loaded in 32-bit, 16-bit, 8-bit, and 4-bit modes
34
+
35
+ ```
36
+ python server.py --cpu
37
+ python server.py
38
+ python server.py --load-in-8bit
39
+ python server.py --wbits 4
40
+ ```
41
+
42
+ #### The web UI works with any version of GPTQ-for-LLaMa
43
+
44
+ Including the up to date triton and cuda branches. But you have to delete the `repositories/GPTQ-for-LLaMa` folder and reinstall the new one every time:
45
+
46
+ ```
47
+ cd text-generation-webui/repositories
48
+ rm -r GPTQ-for-LLaMa
49
+ pip uninstall quant-cuda
50
+ git clone https://github.com/oobabooga/GPTQ-for-LLaMa -b cuda # or any other repository and branch
51
+ cd GPTQ-for-LLaMa
52
+ python setup_cuda.py install
53
+ ```
54
+
55
+ #### Instruction-following templates are represented as chat characters
56
+
57
+ https://github.com/oobabooga/text-generation-webui/tree/main/characters/instruction-following
58
+
59
+ #### The right way to run Alpaca, Open Assistant, Vicuna, etc is Instruct mode, not normal chat mode
60
+
61
+ Otherwise the prompt will not be formatted correctly.
62
+
63
+ 1. Start the web UI with
64
+
65
+ ```
66
+ python server.py --chat
67
+ ```
68
+
69
+ 2. Click on the "instruct" option under "Chat modes"
70
+
71
+ 3. Select the correct template in the hidden dropdown menu that will become visible.
72
+
73
+ #### Notebook mode is best mode
74
+
75
+ Ascended individuals have realized that notebook mode is the superset of chat mode and can do chats with ultimate flexibility, including group chats, editing replies, starting a new bot reply in a given way, and impersonating.
76
+
77
+ #### RWKV is a RNN
78
+
79
+ Most models are transformers, but not RWKV, which is a RNN. It's a great model.
80
+
81
+ #### `--gpu-memory` is not a hard limit on the GPU memory
82
+
83
+ It is simply a parameter that is passed to the `accelerate` library while loading the model. More memory will be allocated during generation. That's why this parameter has to be set to less than your total GPU memory.
84
+
85
+ #### Contrastive search perhaps the best preset
86
+
87
+ But it uses a ton of VRAM.
88
+
89
+ #### You can check the sha256sum of downloaded models with the download script
90
+
91
+ ```
92
+ python download-model.py facebook/galactica-125m --check
93
+ ```
94
+
95
+ #### The download script continues interrupted downloads by default
96
+
97
+ It doesn't start over.
98
+
99
+ #### You can download models with multiple threads
100
+
101
+ ```
102
+ python download-model.py facebook/galactica-125m --threads 8
103
+ ```
104
+
105
+ #### LoRAs work in 4-bit mode
106
+
107
+ You need to follow [these instructions](GPTQ-models-(4-bit-mode).md#using-loras-in-4-bit-mode) and then start the web UI with the `--monkey-patch` flag.
docs/System-requirements.md ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ These are the VRAM and RAM requirements (in MiB) to run some examples of models **in 16-bit (default) precision**:
2
+
3
+ | model | VRAM (GPU) | RAM |
4
+ |:-----------------------|-------------:|--------:|
5
+ | arxiv_ai_gpt2 | 1512.37 | 5824.2 |
6
+ | blenderbot-1B-distill | 2441.75 | 4425.91 |
7
+ | opt-1.3b | 2509.61 | 4427.79 |
8
+ | gpt-neo-1.3b | 2605.27 | 5851.58 |
9
+ | opt-2.7b | 5058.05 | 4863.95 |
10
+ | gpt4chan_model_float16 | 11653.7 | 4437.71 |
11
+ | gpt-j-6B | 11653.7 | 5633.79 |
12
+ | galactica-6.7b | 12697.9 | 4429.89 |
13
+ | opt-6.7b | 12700 | 4368.66 |
14
+ | bloomz-7b1-p3 | 13483.1 | 4470.34 |
15
+
16
+ #### GPU mode with 8-bit precision
17
+
18
+ Allows you to load models that would not normally fit into your GPU. Enabled by default for 13b and 20b models in this web UI.
19
+
20
+ | model | VRAM (GPU) | RAM |
21
+ |:---------------|-------------:|--------:|
22
+ | opt-13b | 12528.1 | 1152.39 |
23
+ | gpt-neox-20b | 20384 | 2291.7 |
24
+
25
+ #### CPU mode (32-bit precision)
26
+
27
+ A lot slower, but does not require a GPU.
28
+
29
+ On my i5-12400F, 6B models take around 10-20 seconds to respond in chat mode, and around 5 minutes to generate a 200 tokens completion.
30
+
31
+ | model | RAM |
32
+ |:-----------------------|---------:|
33
+ | arxiv_ai_gpt2 | 4430.82 |
34
+ | gpt-neo-1.3b | 6089.31 |
35
+ | opt-1.3b | 8411.12 |
36
+ | blenderbot-1B-distill | 8508.16 |
37
+ | opt-2.7b | 14969.3 |
38
+ | bloomz-7b1-p3 | 21371.2 |
39
+ | gpt-j-6B | 24200.3 |
40
+ | gpt4chan_model | 24246.3 |
41
+ | galactica-6.7b | 26561.4 |
42
+ | opt-6.7b | 29596.6 |
docs/Training-LoRAs.md ADDED
@@ -0,0 +1,174 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ## Training Your Own LoRAs
2
+
3
+ The WebUI seeks to make training your own LoRAs as easy as possible. It comes down to just a few simple steps:
4
+
5
+ ### **Step 1**: Make a plan.
6
+ - What base model do you want to use? The LoRA you make has to be matched up to a single architecture (eg LLaMA-13B) and cannot be transferred to others (eg LLaMA-7B, StableLM, etc. would all be different). Derivatives of the same model (eg Alpaca finetune of LLaMA-13B) might be transferrable, but even then it's best to train exactly on what you plan to use.
7
+ - What model format do you want? At time of writing, 8-bit models are most stable, and 4-bit are supported but experimental. In the near future it is likely that 4-bit will be the best option for most users.
8
+ - What are you training it on? Do you want it to learn real information, a simple format, ...?
9
+
10
+ ### **Step 2**: Gather a dataset.
11
+ - If you use a dataset similar to the [Alpaca](https://github.com/gururise/AlpacaDataCleaned/blob/main/alpaca_data_cleaned.json) format, that is natively supported by the `Formatted Dataset` input in the WebUI, with premade formatter options.
12
+ - If you use a dataset that isn't matched to Alpaca's format, but uses the same basic JSON structure, you can make your own format file by copying `training/formats/alpaca-format.json` to a new file and [editing its content](#format-files).
13
+ - If you can get the dataset into a simple text file, that works too! You can train using the `Raw text file` input option.
14
+ - This means you can for example just copy/paste a chatlog/documentation page/whatever you want, shove it in a plain text file, and train on it.
15
+ - If you use a structured dataset not in this format, you may have to find an external way to convert it - or open an issue to request native support.
16
+
17
+ ### **Step 3**: Do the training.
18
+ - **3.1**: Load the WebUI, and your model.
19
+ - Make sure you don't have any LoRAs already loaded (unless you want to train for multi-LoRA usage).
20
+ - **3.2**: Open the `Training` tab at the top, `Train LoRA` sub-tab.
21
+ - **3.3**: Fill in the name of the LoRA, select your dataset in the dataset options.
22
+ - **3.4**: Select other parameters to your preference. See [parameters below](#parameters).
23
+ - **3.5**: click `Start LoRA Training`, and wait.
24
+ - It can take a few hours for a large dataset, or just a few minute if doing a small run.
25
+ - You may want to monitor your [loss value](#loss) while it goes.
26
+
27
+ ### **Step 4**: Evaluate your results.
28
+ - Load the LoRA under the Models Tab.
29
+ - You can go test-drive it on the `Text generation` tab, or you can use the `Perplexity evaluation` sub-tab of the `Training` tab.
30
+ - If you used the `Save every n steps` option, you can grab prior copies of the model from sub-folders within the LoRA model's folder and try them instead.
31
+
32
+ ### **Step 5**: Re-run if you're unhappy.
33
+ - Make sure to unload the LoRA before training it.
34
+ - You can simply resume a prior run - use `Copy parameters from` to select your LoRA, and edit parameters. Note that you cannot change the `Rank` of an already created LoRA.
35
+ - If you want to resume from a checkpoint saved along the way, simply copy the contents of the checkpoint folder into the LoRA's folder.
36
+ - (Note: `adapter_model.bin` is the important file that holds the actual LoRA content).
37
+ - This will start Learning Rate and Steps back to the start. If you want to resume as if you were midway through, you can adjust your Learning Rate to the last reported LR in logs and reduce your epochs.
38
+ - Or, you can start over entirely if you prefer.
39
+ - If your model is producing corrupted outputs, you probably need to start over and use a lower Learning Rate.
40
+ - If your model isn't learning detailed information but you want it to, you might need to just run more epochs, or you might need a higher Rank.
41
+ - If your model is enforcing a format you didn't want, you may need to tweak your dataset, or start over and not train as far.
42
+
43
+ ## Format Files
44
+
45
+ If using JSON formatted datasets, they are presumed to be in the following approximate format:
46
+
47
+ ```json
48
+ [
49
+ {
50
+ "somekey": "somevalue",
51
+ "key2": "value2"
52
+ },
53
+ {
54
+ // etc
55
+ }
56
+ ]
57
+ ```
58
+
59
+ Where the keys (eg `somekey`, `key2` above) are standardized, and relatively consistent across the dataset, and the values (eg `somevalue`, `value2`) contain the content actually intended to be trained.
60
+
61
+ For Alpaca, the keys are `instruction`, `input`, and `output`, wherein `input` is sometimes blank.
62
+
63
+ A simple format file for Alpaca to be used as a chat bot is:
64
+
65
+ ```json
66
+ {
67
+ "instruction,output": "User: %instruction%\nAssistant: %output%",
68
+ "instruction,input,output": "User: %instruction%: %input%\nAssistant: %output%"
69
+ }
70
+ ```
71
+
72
+ Note that the keys (eg `instruction,output`) are a comma-separated list of dataset keys, and the values are a simple string that use those keys with `%%`.
73
+
74
+ So for example if a dataset has `"instruction": "answer my question"`, then the format file's `User: %instruction%\n` will be automatically filled in as `User: answer my question\n`.
75
+
76
+ If you have different sets of key inputs, you can make your own format file to match it. This format-file is designed to be as simple as possible to enable easy editing to match your needs.
77
+
78
+ ## Raw Text File Settings
79
+
80
+ When using raw text files as your dataset, the text is automatically split into chunks based on your `Cutoff Length` you get a few basic options to configure them.
81
+ - `Overlap Length` is how much to overlap chunks by. Overlapping chunks helps prevent the model from learning strange mid-sentence cuts, and instead learn continual sentences that flow from earlier text.
82
+ - `Prefer Newline Cut Length` sets a maximum distance in characters to shift the chunk cut towards newlines. Doing this helps prevent lines from starting or ending mid-sentence, preventing the model from learning to cut off sentences randomly.
83
+ - `Hard Cut String` sets a string that indicates there must be a hard cut without overlap. This defaults to `\n\n\n`, meaning 3 newlines. No trained chunk will ever contain this string. This allows you to insert unrelated sections of text in the same text file, but still ensure the model won't be taught to randomly change the subject.
84
+
85
+ ## Parameters
86
+
87
+ The basic purpose and function of each parameter is documented on-page in the WebUI, so read through them in the UI to understand your options.
88
+
89
+ That said, here's a guide to the most important parameter choices you should consider:
90
+
91
+ ### VRAM
92
+
93
+ - First, you must consider your VRAM availability.
94
+ - Generally, under default settings, VRAM usage for training with default parameters is very close to when generating text (with 1000+ tokens of context) (ie, if you can generate text, you can train LoRAs).
95
+ - Note: worse by default in the 4-bit monkeypatch currently. Reduce `Micro Batch Size` to `1` to restore this to expectations.
96
+ - If you have VRAM to spare, setting higher batch sizes will use more VRAM and get you better quality training in exchange.
97
+ - If you have large data, setting a higher cutoff length may be beneficial, but will cost significant VRAM. If you can spare some, set your batch size to `1` and see how high you can push your cutoff length.
98
+ - If you're low on VRAM, reducing batch size or cutoff length will of course improve that.
99
+ - Don't be afraid to just try it and see what happens. If it's too much, it will just error out, and you can lower settings and try again.
100
+
101
+ ### Rank
102
+
103
+ - Second, you want to consider the amount of learning you want.
104
+ - For example, you may wish to just learn a dialogue format (as in the case of Alpaca) in which case setting a low `Rank` value (32 or lower) works great.
105
+ - Or, you might be training on project documentation you want the bot to understand and be able to understand questions about, in which case the higher the rank, the better.
106
+ - Generally, higher Rank = more precise learning = more total content learned = more VRAM usage while training.
107
+
108
+ ### Learning Rate and Epochs
109
+
110
+ - Third, how carefully you want it to be learned.
111
+ - In other words, how okay or not you are with the model losing unrelated understandings.
112
+ - You can control this with 3 key settings: the Learning Rate, its scheduler, and your total epochs.
113
+ - The learning rate controls how much change is made to the model by each token it sees.
114
+ - It's in scientific notation normally, so for example `3e-4` means `3 * 10^-4` which is `0.0003`. The number after `e-` controls how many `0`s are in the number.
115
+ - Higher values let training run faster, but also are more likely to corrupt prior data in the model.
116
+ - You essentially have two variables to balance: the LR, and Epochs.
117
+ - If you make LR higher, you can set Epochs equally lower to match. High LR + low epochs = very fast, low quality training.
118
+ - If you make LR low, set epochs high. Low LR + high epochs = slow but high-quality training.
119
+ - The scheduler controls change-over-time as you train - it starts high, and then goes low. This helps balance getting data in, and having decent quality, at the same time.
120
+ - You can see graphs of the different scheduler options [in the HuggingFace docs here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_1/en/main_classes/optimizer_schedules#transformers.SchedulerType)
121
+
122
+ ## Loss
123
+
124
+ When you're running training, the WebUI's console window will log reports that include, among other things, a numeric value named `Loss`. It will start as a high number, and gradually get lower and lower as it goes.
125
+
126
+ "Loss" in the world of AI training theoretically means "how close is the model to perfect", with `0` meaning "absolutely perfect". This is calculated by measuring the difference between the model outputting exactly the text you're training it to output, and what it actually outputs.
127
+
128
+ In practice, a good LLM should have a very complex variable range of ideas running in its artificial head, so a loss of `0` would indicate that the model has broken and forgotten to how think about anything other than what you trained it.
129
+
130
+ So, in effect, Loss is a balancing game: you want to get it low enough that it understands your data, but high enough that it isn't forgetting everything else. Generally, if it goes below `1.0`, it's going to start forgetting its prior memories, and you should stop training. In some cases you may prefer to take it as low as `0.5` (if you want it to be very very predictable). Different goals have different needs, so don't be afraid to experiment and see what works best for you.
131
+
132
+ Note: if you see Loss start at or suddenly jump to exactly `0`, it is likely something has gone wrong in your training process (eg model corruption).
133
+
134
+ ## Note: 4-Bit Monkeypatch
135
+
136
+ The [4-bit LoRA monkeypatch](GPTQ-models-(4-bit-mode).md#using-loras-in-4-bit-mode) works for training, but has side effects:
137
+ - VRAM usage is higher currently. You can reduce the `Micro Batch Size` to `1` to compensate.
138
+ - Models do funky things. LoRAs apply themselves, or refuse to apply, or spontaneously error out, or etc. It can be helpful to reload base model or restart the WebUI between training/usage to minimize chances of anything going haywire.
139
+ - Loading or working with multiple LoRAs at the same time doesn't currently work.
140
+ - Generally, recognize and treat the monkeypatch as the dirty temporary hack it is - it works, but isn't very stable. It will get better in time when everything is merged upstream for full official support.
141
+
142
+ ## Legacy notes
143
+
144
+ LoRA training was contributed by [mcmonkey4eva](https://github.com/mcmonkey4eva) in PR [#570](https://github.com/oobabooga/text-generation-webui/pull/570).
145
+
146
+ ### Using the original alpaca-lora code
147
+
148
+ Kept here for reference. The Training tab has much more features than this method.
149
+
150
+ ```
151
+ conda activate textgen
152
+ git clone https://github.com/tloen/alpaca-lora
153
+ ```
154
+
155
+ Edit those two lines in `alpaca-lora/finetune.py` to use your existing model folder instead of downloading everything from decapoda:
156
+
157
+ ```
158
+ model = LlamaForCausalLM.from_pretrained(
159
+ "models/llama-7b",
160
+ load_in_8bit=True,
161
+ device_map="auto",
162
+ )
163
+ tokenizer = LlamaTokenizer.from_pretrained(
164
+ "models/llama-7b", add_eos_token=True
165
+ )
166
+ ```
167
+
168
+ Run the script with:
169
+
170
+ ```
171
+ python finetune.py
172
+ ```
173
+
174
+ It just works. It runs at 22.32s/it, with 1170 iterations in total, so about 7 hours and a half for training a LoRA. RTX 3090, 18153MiB VRAM used, drawing maximum power (350W, room heater mode).
docs/WSL-installation-guide.md ADDED
@@ -0,0 +1,82 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Guide created by [@jfryton](https://github.com/jfryton). Thank you jfryton.
2
+
3
+ -----
4
+
5
+ Here's an easy-to-follow, step-by-step guide for installing Windows Subsystem for Linux (WSL) with Ubuntu on Windows 10/11:
6
+
7
+ ## Step 1: Enable WSL
8
+
9
+ 1. Press the Windows key + X and click on "Windows PowerShell (Admin)" or "Windows Terminal (Admin)" to open PowerShell or Terminal with administrator privileges.
10
+ 2. In the PowerShell window, type the following command and press Enter:
11
+
12
+ ```
13
+ wsl --install
14
+ ```
15
+
16
+ If this command doesn't work, you can enable WSL with the following command for Windows 10:
17
+
18
+ ```
19
+ wsl --set-default-version 1
20
+ ```
21
+
22
+ For Windows 11, you can use:
23
+
24
+ ```
25
+ wsl --set-default-version 2
26
+ ```
27
+
28
+ You may be prompted to restart your computer. If so, save your work and restart.
29
+
30
+ ## Step 2: Install Ubuntu
31
+
32
+ 1. Open the Microsoft Store.
33
+ 2. Search for "Ubuntu" in the search bar.
34
+ 3. Choose the desired Ubuntu version (e.g., Ubuntu 20.04 LTS) and click "Get" or "Install" to download and install the Ubuntu app.
35
+ 4. Once the installation is complete, click "Launch" or search for "Ubuntu" in the Start menu and open the app.
36
+
37
+ ## Step 3: Set up Ubuntu
38
+
39
+ 1. When you first launch the Ubuntu app, it will take a few minutes to set up. Be patient as it installs the necessary files and sets up your environment.
40
+ 2. Once the setup is complete, you will be prompted to create a new UNIX username and password. Choose a username and password, and make sure to remember them, as you will need them for future administrative tasks within the Ubuntu environment.
41
+
42
+ ## Step 4: Update and upgrade packages
43
+
44
+ 1. After setting up your username and password, it's a good idea to update and upgrade your Ubuntu system. Run the following commands in the Ubuntu terminal:
45
+
46
+ ```
47
+ sudo apt update
48
+ sudo apt upgrade
49
+ ```
50
+
51
+ 2. Enter your password when prompted. This will update the package list and upgrade any outdated packages.
52
+
53
+ Congratulations! You have now installed WSL with Ubuntu on your Windows 10/11 system. You can use the Ubuntu terminal for various tasks, like running Linux commands, installing packages, or managing files.
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+
55
+ You can launch your WSL Ubuntu installation by selecting the Ubuntu app (like any other program installed on your computer) or typing 'ubuntu' into Powershell or Terminal.
56
+
57
+ ## Step 5: Proceed with Linux instructions
58
+
59
+ 1. You can now follow the Linux setup instructions. If you receive any error messages about a missing tool or package, just install them using apt:
60
+
61
+ ```
62
+ sudo apt install [missing package]
63
+ ```
64
+
65
+ You will probably need to install build-essential
66
+
67
+ ```
68
+ sudo apt install build-essential
69
+ ```
70
+
71
+ If you face any issues or need to troubleshoot, you can always refer to the official Microsoft documentation for WSL: https://docs.microsoft.com/en-us/windows/wsl/
72
+
73
+ #### WSL2 performance using /mnt:
74
+ when you git clone a repository, put it inside WSL and not outside. To understand more, take a look at this [issue](https://github.com/microsoft/WSL/issues/4197#issuecomment-604592340)
75
+
76
+ ## Bonus: Port Forwarding
77
+
78
+ By default, you won't be able to access the webui from another device on your local network. You will need to setup the appropriate port forwarding using the following command (using PowerShell or Terminal with administrator privileges).
79
+
80
+ ```
81
+ netsh interface portproxy add v4tov4 listenaddress=0.0.0.0 listenport=7860 connectaddress=localhost connectport=7860
82
+ ```
docs/Windows-installation-guide.md ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ If you are having trouble following the installation instructions in the README, Reddit user [Technical_Leather949](https://www.reddit.com/user/Technical_Leather949/) has created a more detailed, step-by-step guide covering:
2
+
3
+ * Windows installation
4
+ * 8-bit mode on Windows
5
+ * LLaMA
6
+ * LLaMA 4-bit
7
+
8
+ The guide can be found here: https://www.reddit.com/r/LocalLLaMA/comments/11o6o3f/how_to_install_llama_8bit_and_4bit/
9
+