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1from transformers import AutoProcessor, Qwen2VLForConditionalGeneration
2
3from llmcompressor.modifiers.quantization import QuantizationModifier
4from llmcompressor.transformers import oneshot, wrap_hf_model_class
5
6MODEL_ID = "adamo1139/Qwen2-VL-7B-Sydney"
7
8# Load model.
9model_class = wrap_hf_model_class(Qwen2VLForConditionalGeneration)
10model = model_class.from_pretrained(MODEL_ID, device_map="auto", torch_dtype="auto")
11processor = AutoProcessor.from_pretrained(MODEL_ID)
12
13# Configure the simple PTQ quantization
14recipe = QuantizationModifier(
15 targets="Linear",
16 scheme="FP8_DYNAMIC",
17 ignore=["re:.*lm_head", "re:visual.*"]
18)
19
20# Apply the quantization algorithm.
21oneshot(model=model, recipe=recipe)
22
23# Save the model.
24SAVE_DIR = MODEL_ID.split("/")[1] + "-FP8-Dynamic"
25model.save_pretrained(SAVE_DIR)
26processor.save_pretrained(SAVE_DIR)