| --- |
| license: other |
| datasets: |
| - ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered |
| inference: false |
| --- |
| |
| # WizardLM - uncensored: An Instruction-following LLM Using Evol-Instruct |
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| These files are GGML format model files for [Eric Hartford's 'uncensored' version of WizardLM](ehartford/WizardLM-7B-Uncensored). |
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| GGML files are for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp). |
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| Eric did a fresh 7B training using the WizardLM method, on [a dataset edited to remove all the "I'm sorry.." type ChatGPT responses](https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered). |
|
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| ## Other repositories available |
|
|
| * [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GPTQ) |
| * [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGML) |
| * [Eric's unquantised model in HF format](https://huggingface.co/ehartford/WizardLM-7B-Uncensored) |
|
|
| ## 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 |
| | Name | Quant method | Bits | Size | RAM required | Use case | |
| | ---- | ---- | ---- | ---- | ---- | ----- | |
| `WizardLM-7B-uncensored.q4_0.bin` | q4_0 | 4bit | 4.2GB | 6GB | 4-bit. | |
| `WizardLM-7B-uncensored.q4_1.bin` | q4_1 | 4bit | 4.63GB | 6GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.| |
| `WizardLM-7B-uncensored.q5_0.bin` | q5_0 | 5bit | 4.63GB | 7GB | 5-bit. Higher accuracy, higher resource usage and slower inference. | |
| `WizardLM-7B-uncensored.q5_1.bin` | q5_1 | 5bit | 5.0GB | 7GB | 5-bit. Even higher accuracy, resource usage and slower inference.| |
| `WizardLM-7B-uncensored.q8_0.bin` | q8_0 | 5bit | 9.0GB | 11 | 5-bit. Even higher accuracy, resource usage and slower inference.| |
| |
| ## How to run in `llama.cpp` |
| |
| I use the following command line; adjust for your tastes and needs: |
| |
| ``` |
| ./main -t 12 -m WizardLM-7B-uncensored.ggmlv3.q4_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request. |
| ### Instruction: |
| Write a story about llamas |
| ### Response:" |
| ``` |
| Change `-t 12` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`. |
| |
| If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins` |
| |
| ## How to run in `text-generation-webui` |
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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). |
| |
| 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. |
|
|
| # Eric's original model card |
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| This is WizardLM trained with a subset of the dataset - responses that contained alignment / moralizing were removed. The intent is to train a WizardLM that doesn't have alignment built-in, so that alignment (of any sort) can be added separately with for example with a RLHF LoRA. |
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| Shout out to the open source AI/ML community, and everyone who helped me out, including Rohan, TheBloke, and Caseus |
|
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| # WizardLM's original model card |
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| Overview of Evol-Instruct |
| Evol-Instruct is a novel method using LLMs instead of humans to automatically mass-produce open-domain instructions of various difficulty levels and skills range, to improve the performance of LLMs. |
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