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Update README.md

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  1. README.md +6 -4
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@@ -8,7 +8,7 @@ base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
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  - ## Introduction
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  This model was created by applying [Quark](https://quark.docs.amd.com/latest/index.html) with calibration samples from Pile dataset.
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  - ## Quantization Stragegy
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- - ***Quantized Layers***: All linear layers excluding "lm_head", "*gate"
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  - ***Weight***: FP8 symmetric per-tensor
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  - ***Activation***: FP8 symmetric per-tensor
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  - ***KV Cache***: FP8 symmetric per-tensor
@@ -23,16 +23,18 @@ python3 quantize_quark.py \
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  --output_dir Mixtral-8x7B-Instruct-v0.1-FP8-KV \
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  --quant_scheme w_fp8_a_fp8 \
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  --kv_cache_dtype fp8 \
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- --num_calib_data 128 \
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- --model_export quark_safetensors
 
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  # If model size is too large for single GPU, please use multi GPU instead.
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  python3 quantize_quark.py \
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  --model_dir $MODEL_DIR \
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  --output_dir Mixtral-8x7B-Instruct-v0.1-FP8-KV \
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  --quant_scheme w_fp8_a_fp8 \
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  --kv_cache_dtype fp8 \
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- --num_calib_data 128 \
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  --model_export quark_safetensors \
 
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  --multi_gpu
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  ```
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  ## Deployment
 
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  - ## Introduction
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  This model was created by applying [Quark](https://quark.docs.amd.com/latest/index.html) with calibration samples from Pile dataset.
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  - ## Quantization Stragegy
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+ - ***Quantized Layers***: All linear layers excluding "lm_head", "*.gate"
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  - ***Weight***: FP8 symmetric per-tensor
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  - ***Activation***: FP8 symmetric per-tensor
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  - ***KV Cache***: FP8 symmetric per-tensor
 
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  --output_dir Mixtral-8x7B-Instruct-v0.1-FP8-KV \
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  --quant_scheme w_fp8_a_fp8 \
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  --kv_cache_dtype fp8 \
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+ --num_calib_data 128 \
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+ --model_export quark_safetensors \
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+ --no_weight_matrix_merge
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  # If model size is too large for single GPU, please use multi GPU instead.
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  python3 quantize_quark.py \
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  --model_dir $MODEL_DIR \
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  --output_dir Mixtral-8x7B-Instruct-v0.1-FP8-KV \
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  --quant_scheme w_fp8_a_fp8 \
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  --kv_cache_dtype fp8 \
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+ --num_calib_data 128 \
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  --model_export quark_safetensors \
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+ --no_weight_matrix_merge \
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  --multi_gpu
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  ```
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  ## Deployment