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README.md
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## Model Details: Neural-Chat-v3-1-int4-inc
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This model is an int4 model with group_size 128 of [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1) generated by [intel/auto-round](https://github.com/intel/auto-round).
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@@ -50,7 +50,7 @@ Install [AutoGPTQ](https://github.com/AutoGPTQ/AutoGPTQ) from source first
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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quantized_model_dir = "Intel/neural-chat-v3-1-int4-inc"
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model = AutoModelForCausalLM.from_pretrained(quantized_model_dir,
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device_map="auto",
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trust_remote_code=False,
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Install [lm-eval-harness](https://github.com/EleutherAI/lm-evaluation-harness.git) from source, we used the git id f3b7917091afba325af3980a35d8a6dcba03dc3f
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```bash
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lm_eval --model hf --model_args pretrained="Intel/neural-chat-v3-1-int4-inc",autogptq=True,gptq_use_triton=True --device cuda:0 --tasks lambada_openai,hellaswag,piqa,winogrande,truthfulqa_mc1,openbookqa,boolq,rte,arc_easy,arc_challenge --batch_size 128
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```
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| Metric | FP16 | INT4 |
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## Model Details: Neural-Chat-7b-v3-1-int4-inc
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This model is an int4 model with group_size 128 of [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1) generated by [intel/auto-round](https://github.com/intel/auto-round).
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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quantized_model_dir = "Intel/neural-chat-7b-v3-1-int4-inc"
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model = AutoModelForCausalLM.from_pretrained(quantized_model_dir,
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device_map="auto",
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trust_remote_code=False,
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Install [lm-eval-harness](https://github.com/EleutherAI/lm-evaluation-harness.git) from source, we used the git id f3b7917091afba325af3980a35d8a6dcba03dc3f
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```bash
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lm_eval --model hf --model_args pretrained="Intel/neural-chat-7b-v3-1-int4-inc",autogptq=True,gptq_use_triton=True --device cuda:0 --tasks lambada_openai,hellaswag,piqa,winogrande,truthfulqa_mc1,openbookqa,boolq,rte,arc_easy,arc_challenge --batch_size 128
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```
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| Metric | FP16 | INT4 |
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