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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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+ ---
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+ language:
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+ - en
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+ - zh
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+ pipeline_tag: text-generation
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+ tags:
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+ - Awq
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+ - int4
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+ - yi1.5-34B-Chat
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+ - pytorch
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+ license: Apache 2.0
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+ license_name: Apache 2.0
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+ license_link: LICENSE
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+ ---
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+
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+ ## About Quantization
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+ 我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行AWQ 4bit量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
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+
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+ We use the modelscope [swift](https://github.com/modelscope/swift/) repository to perform AWQ 4bit quantization. Quantization documentation can be found [here](https://github.com/modelscope/swift/blob/main/docs/source_en/LLM/LLM-quantization.md). The quantization command is as follows:
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+
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+ ```bash
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+ # Experimental Environment: A100
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+ swift export \
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+ --quant_bits 4 \
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+ --model_type yi-1_5-34b-chat \
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+ --quant_method awq \
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+ --quant_n_samples 32 \
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+ --dataset alpaca-zh alpaca-en sharegpt-gpt4-mini \
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+ --quant_seqlen 4096
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+ ```
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+
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+ Inference:
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+ ```bash
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+ CUDA_VISIBLE_DEVICES=0 swift infer --model_type yi-1_5-34b-chat-awq-int4
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+ ```
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+
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+ SFT:
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+ ```bash
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+ CUDA_VISIBLE_DEVICES=0 swift sft --model_type yi-1_5-34b-chat-awq-int4 --dataset leetcode-python-en
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+ ```
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+
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+ Original Model:
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+
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+ [YI1.5-34B-Chat](https://modelscope.cn/models/01ai/Yi-1.5-34B-Chat/summary)
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ },
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+ }
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+ "framework": "Pytorch",
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+ "task": "text-generation"
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