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---
license: apache-2.0
---

Script for creating this. llmcompressor installed from source since it depends on something that wasn't compiled into the release at the time.

```
from transformers import AutoProcessor, Qwen2VLForConditionalGeneration

from llmcompressor.modifiers.quantization import QuantizationModifier
from llmcompressor.transformers import oneshot, wrap_hf_model_class

MODEL_ID = "Qwen/Qwen2-VL-7B-Instruct"

# Load model.
model_class = wrap_hf_model_class(Qwen2VLForConditionalGeneration)
model = model_class.from_pretrained(MODEL_ID, device_map="auto", torch_dtype="auto")
processor = AutoProcessor.from_pretrained(MODEL_ID)

# Configure the simple PTQ quantization
recipe = QuantizationModifier(
  targets="Linear", 
  scheme="FP8_DYNAMIC", 
  ignore=["re:.*lm_head", "re:visual.*"]
)

# Apply the quantization algorithm.
oneshot(model=model, recipe=recipe)

# Save the model.
SAVE_DIR = MODEL_ID.split("/")[1] + "-FP8-Dynamic"
model.save_pretrained(SAVE_DIR)
processor.save_pretrained(SAVE_DIR)
```