--- title: llama2-webui app_file: app_4bit_ggml.py sdk: gradio sdk_version: 3.37.0 --- # llama2-webui Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac). - Supporting all Llama 2 models (7B, 13B, 70B, GPTQ, GGML) with 8-bit, 4-bit mode. - Supporting GPU inference with at least 6 GB VRAM, and CPU inference. ![screenshot](./static/screenshot.png) ## Features - Supporting models: [Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)/[13b](https://huggingface.co/llamaste/Llama-2-13b-chat-hf)/[70b](https://huggingface.co/llamaste/Llama-2-70b-chat-hf), all [Llama-2-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ), all [Llama-2-GGML](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML) ... - Supporting model backends - Nvidia GPU: tranformers, [bitsandbytes(8-bit inference)](https://github.com/TimDettmers/bitsandbytes), [AutoGPTQ(4-bit inference)](https://github.com/PanQiWei/AutoGPTQ) - GPU inference with at least 6 GB VRAM - CPU, Mac/AMD GPU: [llama.cpp](https://github.com/ggerganov/llama.cpp) - CPU inference [Demo](https://twitter.com/liltom_eth/status/1682791729207070720?s=20) on Macbook Air. - Web UI interface: gradio ## Contents - [Install](#install) - [Download Llama-2 Models](#download-llama-2-models) - [Model List](#model-list) - [Download Script](#download-script) - [Usage](#usage) - [Config Examples](#config-examples) - [Start Web UI](#start-web-ui) - [Run on Nvidia GPU](#run-on-nvidia-gpu) - [Run on Low Memory GPU with 8 bit](#run-on-low-memory-gpu-with-8-bit) - [Run on Low Memory GPU with 4 bit](#run-on-low-memory-gpu-with-4-bit) - [Run on CPU](#run-on-cpu) - [Mac GPU and AMD/Nvidia GPU Acceleration](#mac-gpu-and-amdnvidia-gpu-acceleration) - [Benchmark](#benchmark) - [Contributing](#contributing) - [License](#license) ## Install ### Method 1: From [PyPI](https://pypi.org/project/llama2-wrapper/) ``` pip install llama2-wrapper ``` ### Method 2: From Source: ``` git clone https://github.com/liltom-eth/llama2-webui.git cd llama2-webui pip install -r requirements.txt ``` ### Install Issues: `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: - `pip install bitsandbytes==0.38.1` `bitsandbytes` also need a special install for Windows: ``` pip uninstall bitsandbytes pip install https://github.com/jllllll/bitsandbytes-windows-webui/releases/download/wheels/bitsandbytes-0.41.0-py3-none-win_amd64.whl ``` ## Download Llama-2 Models Llama 2 is a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. Llama-2-7b-Chat-GPTQ is the GPTQ model files for [Meta's Llama 2 7b Chat](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf). GPTQ 4-bit Llama-2 model require less GPU VRAM to run it. ### Model List | Model Name | set MODEL_PATH in .env | Download URL | | ------------------------------ | ---------------------------------------- | ------------------------------------------------------------ | | meta-llama/Llama-2-7b-chat-hf | /path-to/Llama-2-7b-chat-hf | [Link](https://huggingface.co/llamaste/Llama-2-7b-chat-hf) | | meta-llama/Llama-2-13b-chat-hf | /path-to/Llama-2-13b-chat-hf | [Link](https://huggingface.co/llamaste/Llama-2-13b-chat-hf) | | meta-llama/Llama-2-70b-chat-hf | /path-to/Llama-2-70b-chat-hf | [Link](https://huggingface.co/llamaste/Llama-2-70b-chat-hf) | | meta-llama/Llama-2-7b-hf | /path-to/Llama-2-7b-hf | [Link](https://huggingface.co/meta-llama/Llama-2-7b-hf) | | meta-llama/Llama-2-13b-hf | /path-to/Llama-2-13b-hf | [Link](https://huggingface.co/meta-llama/Llama-2-13b-hf) | | meta-llama/Llama-2-70b-hf | /path-to/Llama-2-70b-hf | [Link](https://huggingface.co/meta-llama/Llama-2-70b-hf) | | TheBloke/Llama-2-7b-Chat-GPTQ | /path-to/Llama-2-7b-Chat-GPTQ | [Link](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ) | | TheBloke/Llama-2-7B-Chat-GGML | /path-to/llama-2-7b-chat.ggmlv3.q4_0.bin | [Link](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML) | | ... | ... | ... | Running 4-bit model `Llama-2-7b-Chat-GPTQ` needs GPU with 6GB VRAM. Running 4-bit model `llama-2-7b-chat.ggmlv3.q4_0.bin` needs CPU with 6GB RAM. There is also a list of other 2, 3, 4, 5, 6, 8-bit GGML models that can be used from [TheBloke/Llama-2-7B-Chat-GGML](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML). ### Download Script These models can be downloaded from the link using CMD like: ```bash # Make sure you have git-lfs installed (https://git-lfs.com) git lfs install git clone git@hf.co:meta-llama/Llama-2-7b-chat-hf ``` To download Llama 2 models, you need to request access from [https://ai.meta.com/llama/](https://ai.meta.com/llama/) and also enable access on repos like [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/tree/main). Requests will be processed in hours. For GPTQ models like [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ), you can directly download without requesting access. For GGML models like [TheBloke/Llama-2-7B-Chat-GGML](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML), you can directly download without requesting access. ## Usage ### Config Examples Setup your `MODEL_PATH` and model configs in `.env` file. There are some examples in `./env_examples/` folder. | Model Setup | Example .env | | --------------------------------- | --------------------------- | | Llama-2-7b-chat-hf 8-bit on GPU | .env.7b_8bit_example | | Llama-2-7b-Chat-GPTQ 4-bit on GPU | .env.7b_gptq_example | | Llama-2-7B-Chat-GGML 4bit on CPU | .env.7b_ggmlv3_q4_0_example | | Llama-2-13b-chat-hf on GPU | .env.13b_example | | ... | ... | ### Start Web UI Run chatbot with web UI: ``` python app.py ``` ### Run on Nvidia GPU The running requires around 14GB of GPU VRAM for Llama-2-7b and 28GB of GPU VRAM for Llama-2-13b. If you are running on multiple GPUs, the model will be loaded automatically on GPUs and split the VRAM usage. That allows you to run Llama-2-7b (requires 14GB of GPU VRAM) on a setup like 2 GPUs (11GB VRAM each). #### Run on Low Memory GPU with 8 bit If you do not have enough memory, you can set up your `LOAD_IN_8BIT` as `True` in `.env`. This can reduce memory usage by around half with slightly degraded model quality. It is compatible with the CPU, GPU, and Metal backend. Llama-2-7b with 8-bit compression can run on a single GPU with 8 GB of VRAM, like an Nvidia RTX 2080Ti, RTX 4080, T4, V100 (16GB). #### Run on Low Memory GPU with 4 bit If you want to run 4 bit Llama-2 model like `Llama-2-7b-Chat-GPTQ`, you can set up your `LOAD_IN_4BIT` as `True` in `.env` like example `.env.7b_gptq_example`. Make sure you have downloaded the 4-bit model from `Llama-2-7b-Chat-GPTQ` and set the `MODEL_PATH` and arguments in `.env` file. `Llama-2-7b-Chat-GPTQ` can run on a single GPU with 6 GB of VRAM. ### Run on CPU Run Llama-2 model on CPU requires [llama.cpp](https://github.com/ggerganov/llama.cpp) dependency and [llama.cpp Python Bindings](https://github.com/abetlen/llama-cpp-python), which are already installed. Download GGML models like `llama-2-7b-chat.ggmlv3.q4_0.bin` following [Download Llama-2 Models](#download-llama-2-models) section. `llama-2-7b-chat.ggmlv3.q4_0.bin` model requires at least 6 GB RAM to run on CPU. Set up configs like `.env.7b_ggmlv3_q4_0_example` from `env_examples` as `.env`. Run web UI `python app.py` . #### Mac GPU and AMD/Nvidia GPU Acceleration If you would like to use Mac GPU and AMD/Nvidia GPU for acceleration, check these: - [Installation with OpenBLAS / cuBLAS / CLBlast / Metal](https://github.com/abetlen/llama-cpp-python#installation-with-openblas--cublas--clblast--metal) - [MacOS Install with Metal GPU](https://github.com/abetlen/llama-cpp-python/blob/main/docs/install/macos.md) ### Benchmark Run benchmark script to compute performance on your device: ```bash python benchmark.py ``` `benchmark.py` will load the same `.env` as `app.py`. Some benchmark performance: | Model | Precision | Device | GPU VRAM | Speed (tokens / sec) | load time (s) | | -------------------- | --------- | ------------------ | ----------- | -------------------- | ------------- | | Llama-2-7b-chat-hf | 8bit | NVIDIA RTX 2080 Ti | 7.7 GB VRAM | 3.76 | 783.87 | | Llama-2-7b-Chat-GPTQ | 4 bit | NVIDIA RTX 2080 Ti | 5.8 GB VRAM | 12.08 | 192.91 | | Llama-2-7B-Chat-GGML | 4 bit | Intel i7-8700 | 5.1GB RAM | 4.16 | 105.75 | Check / contribute the performance of your device in the full [performance doc](./docs/performance.md). ## Contributing Kindly read our [Contributing Guide](CONTRIBUTING.md) to learn and understand about our development process. ### All Contributors ## License MIT - see [MIT License](LICENSE) This project enables users to adapt it freely for proprietary purposes without any restrictions. ## Credits - https://huggingface.co/meta-llama/Llama-2-7b-chat-hf - https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat - https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ - [https://github.com/ggerganov/llama.cpp](https://github.com/ggerganov/llama.cpp) - [https://github.com/TimDettmers/bitsandbytes](https://github.com/TimDettmers/bitsandbytes) - [https://github.com/PanQiWei/AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ)