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--- |
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license: apache-2.0 |
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--- |
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# Molmo 7B-D |
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## Quick Start |
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To run Molmo, first install dependencies: |
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```bash |
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pip install einops torch torchvision PIL |
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``` |
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Then, follow these steps: |
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```python |
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from transformers import AutoModelForCausalLM, AutoProcessor, GenerationConfig |
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from PIL import Image |
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import requests |
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# load the processor |
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processor = AutoProcessor.from_pretrained( |
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'allenai/Molmo-7B-D-0924', |
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trust_remote_code=True, |
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torch_dtype='auto', |
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device_map='auto' |
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) |
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# load the model |
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model = AutoModelForCausalLM.from_pretrained( |
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'allenai/Molmo-7B-D-0924', |
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trust_remote_code=True, |
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torch_dtype='auto', |
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device_map='auto' |
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) |
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# process the image and text |
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inputs = processor.process( |
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images=[Image.open(requests.get("https://picsum.photos/id/237/536/354", stream=True).raw)], |
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text="Describe this image." |
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) |
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# move inputs to the correct device and make a batch of size 1 |
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inputs = {k: v.to(model.device).unsqueeze(0) for k, v in inputs.items()} |
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# generate output; maximum 200 new tokens; stop generation when <|endoftext|> is generated |
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output = model.generate_from_batch( |
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inputs, |
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GenerationConfig(max_new_tokens=200, stop_strings="<|endoftext|>"), |
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tokenizer=processor.tokenizer |
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) |
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# only get generated tokens; decode them to text |
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generated_tokens = output[0,inputs['input_ids'].size(1):] |
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generated_text = processor.tokenizer.decode(generated_tokens, skip_special_tokens=True) |
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# print the generated text |
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print(generated_text) |
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``` |
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