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Create README.md

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+ ---
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+ datasets:
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+ - MMInstruction/M3IT
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+ pipeline_tag: image-to-text
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+ ---
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+
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+ This model is fintuned on instruction dataset using `SalesForce/blip-imagecaptioning-base` model.
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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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+
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+ processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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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/Instruct-blip-v2")
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+
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+ image = Image.open('file_name.jpg').convert('RGB')
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+
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+ prompt = """Instruction: Answer the following input according to the image.
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+ Input: Describe this image.
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+ output: """
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+
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+ inputs = processor(image, prompt, return_tensors="pt")
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+
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+ output = model.generate(**inputs, max_length=100)
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+ print(tokenizer.decode(output[0]))
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+ ```