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--- |
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license: apache-2.0 |
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tags: |
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- finetuned |
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- quantized |
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- 4-bit |
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- gptq |
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- transformers |
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- pytorch |
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- mistral |
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- text-generation |
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- LLMs |
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- math |
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- Intel |
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- en |
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- dataset:meta-math/MetaMathQA |
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- dataset:Intel/orca_dpo_pairs |
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- arxiv:2309.12284 |
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- base_model:meta-math/MetaMath-Mistral-7B |
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- license:apache-2.0 |
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- autotrain_compatible |
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- endpoints_compatible |
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- has_space |
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- text-generation-inference |
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- region:us |
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model_name: neural-chat-7b-v3-3-Slerp-GPTQ |
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base_model: Intel/neural-chat-7b-v3-3-Slerp |
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inference: false |
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model_creator: Intel |
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pipeline_tag: text-generation |
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quantized_by: MaziyarPanahi |
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--- |
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# Description |
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[MaziyarPanahi/neural-chat-7b-v3-3-Slerp-GPTQ](https://huggingface.co/MaziyarPanahi/neural-chat-7b-v3-3-Slerp-GPTQ) is a quantized (GPTQ) version of [Intel/neural-chat-7b-v3-3-Slerp](https://huggingface.co/Intel/neural-chat-7b-v3-3-Slerp) |
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## How to use |
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### Install the necessary packages |
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``` |
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pip install --upgrade accelerate auto-gptq transformers |
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``` |
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### Example Python code |
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```python |
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from transformers import AutoTokenizer, pipeline |
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from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig |
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import torch |
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model_id = "MaziyarPanahi/neural-chat-7b-v3-3-Slerp-GPTQ" |
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quantize_config = BaseQuantizeConfig( |
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bits=4, |
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group_size=128, |
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desc_act=False |
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) |
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model = AutoGPTQForCausalLM.from_quantized( |
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model_id, |
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use_safetensors=True, |
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device="cuda:0", |
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quantize_config=quantize_config) |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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pipe = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer, |
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max_new_tokens=512, |
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temperature=0.7, |
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top_p=0.95, |
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repetition_penalty=1.1 |
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) |
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outputs = pipe("What is a large language model?") |
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print(outputs[0]["generated_text"]) |
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``` |
