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--- |
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pipeline_tag: image-to-text |
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datasets: |
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- MMInstruction/M3IT |
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--- |
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## Usage: |
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``` |
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from transformers import BlipProcessor, BlipForConditionalGeneration |
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import torch |
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from PIL import Image |
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processor = BlipProcessor.from_pretrained("prasanna2003/blip-image-captioning") |
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if processor.tokenizer.eos_token is None: |
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processor.tokenizer.eos_token = '<|eos|>' |
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model = BlipForConditionalGeneration.from_pretrained("prasanna2003/blip-image-captioning") |
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image = Image.open('file_name.jpg').convert('RGB') |
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prompt = """Instruction: Generate a single line caption of the Image. |
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output: """ |
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inputs = processor(image, prompt, return_tensors="pt") |
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output = model.generate(**inputs, max_length=100) |
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print(processor.tokenizer.decode(output[0])) |
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``` |