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--- |
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license: apache-2.0 |
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base_model: |
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- rhymes-ai/Aria-sequential_mlp |
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- rhymes-ai/Aria |
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pipeline_tag: image-text-to-text |
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--- |
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# Aria-sequential_mlp-FP8-dynamic |
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#### Warning: There is no inference code for transformers/vLLM yet! |
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FP8-Dynamic quantization from [Aria-sequential_mlp](https://huggingface.co/rhymes-ai/Aria-sequential_mlp) made with [LLM Compressor](https://github.com/vllm-project/llm-compressor). |
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Generated with the following code: |
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```python |
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from transformers import AutoProcessor, AutoModelForCausalLM |
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from llmcompressor.modifiers.quantization import QuantizationModifier |
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from llmcompressor.transformers import SparseAutoModelForCausalLM, oneshot |
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model_name = "rhymes-ai/Aria-sequential_mlp" |
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model = SparseAutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True) |
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processor = AutoProcessor.from_pretrained(model_name, trust_remote_code=True) |
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recipe = QuantizationModifier( |
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targets="Linear", |
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scheme="FP8_DYNAMIC", |
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ignore=["re:.*lm_head", "re:multi_modal_projector.*", "re:vision_tower.*"], |
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) |
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folder = model_name.split("/")[1] + "-FP8-Dynamic" |
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oneshot(model=model, recipe=recipe, output_dir=folder) |
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processor.save_pretrained(folder) |
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``` |
