haoyang-amd
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Update README.md
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README.md
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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", "
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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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@@ -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
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