Add FramePack example

examples/pytorch/diffusion_model/diffusers/framepack/README.md

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+# Step-by-Step
+
+This example quantizes and validates the accuracy of Flux.
+
+# Prerequisite
+
+## 1. Environment
+
+```shell
+# install zip according to your system
+sudo apt update && sudo apt install zip
+
+pip install -r requirements.txt
+pip install --update neural-compressor-pt
+pip install --update auto-round
+git clone --depth 1 https://github.com/lllyasviel/FramePack.git
+cp -r FramePack/diffusers_helper/ .
+
+# several models will be downloaded automatically into HF_HOME
+export HF_HOME=/path/to/save/model
+```
+
+## 2. Prepare Dataset
+
+```shell
+git clone --depth 1 https://github.com/Vchitect/VBench.git
+cd VBench
+sh vbench2_beta_i2v/download_data.sh
+```
+
+# Run
+
+## BF16
+
+```bash
+CUDA_VISIBLE_DEVICES=0,1,2,3 \
+bash run_benchmark.sh \
+    --topology=BF16 \
+    --dataset_location=/path/to/VBench \
+    --output_video_path=bf16_video \
+    --dimension_list=subject_consistency i2v_background \
+    --result_path=bf16_result
+```
+
+## MXFP8 or FP8 
+
+```bash
+CUDA_VISIBLE_DEVICES=0,1,2,3 \
+bash run_benchmark.sh \
+    --topology=MXFP8 \ # or FP8
+    --dataset_location=/path/to/VBench \
+    --output_video_path=mxfp8_video \
+    --dimension_list=subject_consistency i2v_background \
+    --result_path=mxfp8_result
+```
+
+- CUDA_VISIBLE_DEVICES: distribute the dimension_list to different visible GPUs to speed up the evaluation