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README.md CHANGED
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  ---
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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: apache-2.0
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+ tags:
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+ - image-captioning
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+ languages:
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+ - en
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+ pipeline_tag: image-to-text
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+ datasets:
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+ - michelecafagna26/hl
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+ language:
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+ - en
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+ metrics:
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+ - sacrebleu
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+ - rouge
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+ library_name: transformers
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  ---
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+ ## BLIP-base fine-tuned for Image Capioning on High-Level descriptions of Scenes
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+
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+ [BLIP](https://arxiv.org/abs/2201.12086) base trained on the [HL dataset](https://huggingface.co/datasets/michelecafagna26/hl) for **high-level descriptions of scenes**
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+
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+ ## Model fine-tuning 🏋️‍
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+
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+ Trained for of 10 epochs
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+ lr: 5e−5,
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+ Adam optimizer,
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+ half-precision (fp16)
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+
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+ ## Test set metrics 🧾
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+
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+ | Cider | SacreBLEU | Rouge-L |
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+ |--------|------------|---------|
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+ | 116.70 | 26.46 | 35.30 |
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+
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+ ## Model in Action 🚀
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+
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+ ```python
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+ import requests
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+ from PIL import Image
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+ from transformers import BlipProcessor, BlipForConditionalGeneration
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+
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+ processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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+ model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to("cuda")
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+
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+ img_url = 'https://datasets-server.huggingface.co/assets/michelecafagna26/hl/--/default/train/0/image/image.jpg'
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+ raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
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+
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+
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+ inputs = processor(raw_image, return_tensors="pt").to("cuda")
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+ pixel_values = inputs.pixel_values
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+
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+ generated_ids = model.generate(pixel_values=pixel_values, max_length=50,
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+ do_sample=True,
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+ top_k=120,
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+ top_p=0.9,
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+ early_stopping=True,
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+ num_return_sequences=1)
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+
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+ processor.batch_decode(generated_ids, skip_special_tokens=True)
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+
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+ >>>
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+ ```
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+
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+ ## BibTex and citation info
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+
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+ ```BibTeX
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+ ```
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tokenizer.json ADDED
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