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+ ---
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+ language:
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+ - th
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+ ---
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+ # Thai Image Captioning
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+ Encoder-decoder style image captioning model using [CLIP encoder](https://huggingface.co/openai/clip-vit-base-patch32) and [GPT2](https://huggingface.co/openai-community/gpt2). Trained on Thai language MSCOCO and IPU24 dataset.
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+
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+ # Usage
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+
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+ Use `AutoModel` to load it. Requires `trust_remote_code=True`.
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+ ```python
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+ from transformers import AutoModel, AutoImageProcessor, AutoTokenizer
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+ device = 'cuda'
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+ gen_kwargs = {"max_length": 120, "num_beams": 4}
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+ model_path = 'Natthaphon/thaicapgen-clip-gpt2'
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+ feature_extractor = AutoImageProcessor.from_pretrained(model_path)
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+ tokenizer = AutoTokenizer.from_pretrained(model_path)
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+ model = AutoModel.from_pretrained(model_path, trust_remote_code=True).to(device)
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+ pixel_values = feature_extractor(images=[Image.open(image_path)], return_tensors="pt").pixel_values
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+ pixel_values = pixel_values.to(device)
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+ output_ids = model.generate(pixel_values, **gen_kwargs)
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+ preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
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+ ```
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+
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+ # Acknowledgement
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+ This work is partially supported by the Program Management Unit for Human Resources & Institutional Development, Research and Innovation (PMU-B) [Grant number B04G640107]