Text Generation
Transformers
English
Inference Endpoints
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New GGMLv3 format for breaking llama.cpp change May 19th commit 2d5db48

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@@ -22,28 +22,29 @@ This repo is the result of quantising to 4bit and 5bit GGML for CPU inference us
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  * [4-bit, 5-bit 8-bit GGML models for llama.cpp CPU (+CUDA) inference](https://huggingface.co/TheBloke/wizard-mega-13B-GGML).
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  * [OpenAccess AI Collective's original float16 HF format repo for GPU inference and further conversions](https://huggingface.co/openaccess-ai-collective/wizard-mega-13b).
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- ## THE FILES IN MAIN BRANCH REQUIRES LATEST LLAMA.CPP (May 12th 2023 - commit b9fd7ee)!
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- llama.cpp recently made a breaking change to its quantisation methods.
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- I have quantised the GGML files in this repo with the latest version. Therefore you will require llama.cpp compiled on May 12th or later (commit `b9fd7ee` or later) to use them.
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- As of May 15th, text-generation-webui is now updated for the new GGML formats, so if you have problems loading these files in that UI, please update it to the latest version.
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  ## Provided files
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  | Name | Quant method | Bits | Size | RAM required | Use case |
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  | ---- | ---- | ---- | ---- | ---- | ----- |
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- `wizard-mega-13B.ggml.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10.5GB | 4-bit. |
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- `wizard-mega-13B.ggml.q4_1.bin` | q5_0 | 5bit | 8.95GB | 11.0GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
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- `wizard-mega-13B.ggml.q5_0.bin` | q5_1 | 5bit | 9.76GB | 12.25GB | 5-bit. Even higher accuracy, and higher resource usage and slower inference. |
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- `wizard-mega-13B.ggml.q8_0.bin` | q8_0 | 8bit | 14.6GB | 17GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use. |
 
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  ## How to run in `llama.cpp`
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  I use the following command line; adjust for your tastes and needs:
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  ```
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- ./main -t 8 -m wizard-mega-13B.ggml.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: write a story about llamas ### Response:"
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  ```
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  Change `-t 8` to the number of physical CPU cores you have.
@@ -54,6 +55,8 @@ GGML models can be loaded into text-generation-webui by installing the llama.cpp
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  Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
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  # Original Wizard Mega 13B model card
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  Wizard Mega is a Llama 13B model fine-tuned on the [ShareGPT](https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered), [WizardLM](https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered), and [Wizard-Vicuna](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered) datasets. These particular datasets have all been filtered to remove responses where the model responds with "As an AI language model...", etc or when the model refuses to respond.
 
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  * [4-bit, 5-bit 8-bit GGML models for llama.cpp CPU (+CUDA) inference](https://huggingface.co/TheBloke/wizard-mega-13B-GGML).
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  * [OpenAccess AI Collective's original float16 HF format repo for GPU inference and further conversions](https://huggingface.co/openaccess-ai-collective/wizard-mega-13b).
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+ ## THE FILES IN MAIN BRANCH REQUIRES LATEST LLAMA.CPP (May 19th 2023 - commit 2d5db48)!
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+ llama.cpp recently made another breaking change to its quantisation methods - https://github.com/ggerganov/llama.cpp/pull/1508
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+ I have quantised the GGML files in this repo with the latest version. Therefore you will require llama.cpp compiled on May 19th or later (commit `2d5db48` or later) to use them.
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+ For files compatible with the previous version of llama.cpp, please see branch `previous_llama_ggmlv2`.
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  ## Provided files
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  | Name | Quant method | Bits | Size | RAM required | Use case |
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  | ---- | ---- | ---- | ---- | ---- | ----- |
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+ `wizard-mega-13B.ggmlv3.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10.5GB | 4-bit. |
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+ `wizard-mega-13B.ggmlv3.q4_1.bin` | q5_0 | 5bit | 8.95GB | 11.0GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.|
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+ `wizard-mega-13B.ggmlv3.q5_0.bin` | q5_0 | 5bit | 8.95GB | 11.0GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
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+ `wizard-mega-13B.ggmlv3.q5_1.bin` | q5_1 | 5bit | 9.76GB | 12.25GB | 5-bit. Even higher accuracy, and higher resource usage and slower inference. |
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+ `wizard-mega-13B.ggmlv3.q8_0.bin` | q8_0 | 8bit | 14.6GB | 17GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use. |
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  ## How to run in `llama.cpp`
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  I use the following command line; adjust for your tastes and needs:
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  ```
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+ ./main -t 8 -m wizard-mega-13B.ggmlv3.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: write a story about llamas ### Response:"
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  ```
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  Change `-t 8` to the number of physical CPU cores you have.
 
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  Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
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+ Note: at this time text-generation-webui may not support the new May 19th llama.cpp quantisation methods for q4_0, q4_1 and q8_0 files.
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+
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  # Original Wizard Mega 13B model card
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  Wizard Mega is a Llama 13B model fine-tuned on the [ShareGPT](https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered), [WizardLM](https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered), and [Wizard-Vicuna](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered) datasets. These particular datasets have all been filtered to remove responses where the model responds with "As an AI language model...", etc or when the model refuses to respond.