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--- |
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base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B |
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language: |
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- en |
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license: cc-by-nc-4.0 |
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tags: |
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- text-generation-inference |
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- transformers |
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- quantized |
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- 4-bit |
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- AWQ |
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- text-generation |
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- autotrain_compatible |
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- endpoints_compatible |
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- chatml |
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- mistral |
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model_creator: SanjiWatsuki |
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model_name: Kunoichi-DPO-v2-7B |
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model_type: mistral |
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pipeline_tag: text-generation |
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inference: false |
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--- |
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# SanjiWatsuki/Kunoichi-DPO-v2-7B AWQ |
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- Model creator: [SanjiWatsuki](https://huggingface.co/SanjiWatsuki) |
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- Original model: [Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B) |
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## Model Summary |
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| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | |
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|---|---:|---:|---:|---:|---:| |
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| **Kunoichi-DPO-7B**|**58.4**| 45.08 | 74| 66.99| 47.52| |
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| **Kunoichi-DPO-v2-7B**|**58.31**| 44.85| 75.05| 65.69| 47.65| |
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| [Kunoichi-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-7B)|57.54| 44.99| 74.86| 63.72| 46.58| |
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| [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)| 56.85 | 44.74 | 75.6 | 59.89 | 47.17 | |
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| [Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B) | 56.45| 44.74| 74.26| 61.5| 45.32| |
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| [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) | 53.51 | 43.67 | 73.24 | 55.37 | 41.76 | |
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| [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 | |
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| [openchat/openchat_3.5](https://huggingface.co/openchat/openchat_3.5) | 51.34 | 42.67 | 72.92 | 47.27 | 42.51 | |
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| [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha) | 51.16 | 42.06 | 72.72 | 47.33 | 42.53 | |
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| [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) | 50.99 | 37.33 | 71.83 | 55.1 | 39.7 | |
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## How to use |
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### Install the necessary packages |
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```bash |
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pip install --upgrade autoawq autoawq-kernels |
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``` |
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### Example Python code |
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```python |
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from awq import AutoAWQForCausalLM |
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from transformers import AutoTokenizer, TextStreamer |
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model_path = "solidrust/Kunoichi-DPO-v2-7B-AWQ" |
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system_message = "You are Kunoichi, incarnated as a powerful AI." |
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# Load model |
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model = AutoAWQForCausalLM.from_quantized(model_path, |
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fuse_layers=True) |
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tokenizer = AutoTokenizer.from_pretrained(model_path, |
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trust_remote_code=True) |
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streamer = TextStreamer(tokenizer, |
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skip_prompt=True, |
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skip_special_tokens=True) |
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# Convert prompt to tokens |
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prompt_template = """\ |
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<|im_start|>system |
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{system_message}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant""" |
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prompt = "You're standing on the surface of the Earth. "\ |
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"You walk one mile south, one mile west and one mile north. "\ |
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"You end up exactly where you started. Where are you?" |
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tokens = tokenizer(prompt_template.format(system_message=system_message,prompt=prompt), |
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return_tensors='pt').input_ids.cuda() |
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# Generate output |
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generation_output = model.generate(tokens, |
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streamer=streamer, |
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max_new_tokens=512) |
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``` |
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### About AWQ |
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AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings. |
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AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead. |
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It is supported by: |
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- [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ |
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- [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types. |
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- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference) |
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- [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers |
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- [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code |
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## Prompt template: ChatML |
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```plaintext |
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<|im_start|>system |
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{system_message}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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``` |
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