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README.md
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More information needed
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## Intended uses & limitations
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More information needed
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More information needed
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## Usage
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```python
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import torch
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from PIL import Image
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from transformers import AutoProcessor, AutoModelForCausalLM
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import requests
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# Load model directly
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processor = AutoProcessor.from_pretrained("tonyassi/git-base-lucy1")
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model = AutoModelForCausalLM.from_pretrained("tonyassi/git-base-lucy1")
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# Load image
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url = "https://datasets-server.huggingface.co/cached-assets/tonyassi/lucy-caption-2/--/94d2ffc965a7a0a50beebbeb60d04fa38a24ff66/--/default/train/6/image/image.jpg?Expires=1727109954&Signature=IMpoIBQV-ICPaC8V4NF2SUn0OQE7cOtIJZIeGSpOQLifkjlXl3rx6CAukc2Ax3Gkl4eQ3BfcDrnV2HNzE-c3c5WC5lcj30PWTkSczcqN7YtkKGFHOxlS6-Gv8zotQw8NJPn0d-LoCERHlxA75Sbh8vF8X6DE1SCRJIitT3DFcObTdKpZpHYDv21BYq4-A4EN04wX6aKHWyz8xR0NorlOtcB8dzPdsSpRGy3gcgLU9kHeBNWpa22KsMDJmDP8QferzrnG5bnb5fi9RxrMCTURCPUB8AyNJ1mVwuAorW4GJIdm40UEoqanQzrST3hIp-dTEH47w5-GY5PnOrWUcaxYGQ__&Key-Pair-Id=K3EI6M078Z3AC3"
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image = Image.open(requests.get(url, stream=True).raw)
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# GPU or CPU
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Inference
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inputs = processor(images=image, return_tensors="pt").to(device)
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pixel_values = inputs.pixel_values
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generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
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generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(generated_caption)
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```
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## Intended uses & limitations
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More information needed
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