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Uploading AWQ model

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README.md CHANGED
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  ---
 
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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ base_model: senseable/WestLake-7B-v2
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  license: apache-2.0
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+ datasets:
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+ - cognitivecomputations/samantha-data
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+ library_name: transformers
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+ model_creator: cognitivecomputations
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+ model_name: Samantha 1.1 WestLake 7B - AWQ
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+ model_type: mistral
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+ pipeline_tag: text-generation
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+ prompt_template: '<|im_start|>system
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+
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+ {system_message}<|im_end|>
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+
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+ <|im_start|>user
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+
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+ {prompt}<|im_end|>
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+
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+ <|im_start|>assistant
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+
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+ '
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+ quantized_by: Suparious
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  ---
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+ # Samantha 7B v1.1 laser - AWQ
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+
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+ - Model creator: [cognitivecomputations](https://huggingface.co/cognitivecomputations)
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+ - Original model: [WestLake 7B v2](https://huggingface.co/cognitivecomputations/WestLake-7B-v2)
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+ - Fine Tuning: [cognitivecomputations](https://huggingface.co/cognitivecomputations/samantha-1.1-westlake-7b-laser)
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+
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+ It follows the implementation of [laserRMT](https://github.com/cognitivecomputations/laserRMT)
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/DQ2iBVPM1PA4GKQBgvMEO.png)
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+
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+ ## Model description
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+
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+ This repo contains AWQ model files for [cognitivecomputations's Samantha 7B v1.1](https://huggingface.co/cognitivecomputations/samantha-1.1-westlake-7b-laser).
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+
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+ These files were quantised using hardware kindly provided by [SolidRusT Networks](https://solidrust.net/).
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+
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+ ### About AWQ
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+
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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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+
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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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+
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+ It is supported by:
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+
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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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+
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+ ## Prompt template: ChatML
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+
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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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+
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+ Also working with Basic Mistral format:
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+
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+ ```plaintext
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+ <|system|>
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+ </s>
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+ <|user|>
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+ {prompt}</s>
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+ <|assistant|>
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+ ```
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+ "quantization_config": {
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+ "bits": 4,
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+ "group_size": 128,
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+ "quant_method": "awq",
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+ "version": "gemm",
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+ "zero_point": true
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ }
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