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@@ -11,6 +11,42 @@ model-index:
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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  # git-base-pokemon
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  This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ #dataset used: polinaeterna/pokemon-blip-captions
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+
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+ #code
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+ ```python
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+
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+ from transformers import AutoProcessor, AutoModelForCausalLM
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+ import torch
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+ from PIL import Image
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+ import requests
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+
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+ #Preprocess the dataset
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+ #Since the dataset has two modalities (image and text), the pre-processing pipeline will preprocess images and the captions.
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+ #To do so, load the processor class associated with the model you are about to fine-tune.
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+
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+ from transformers import AutoProcessor
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+
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+ checkpoint = "microsoft/git-base"
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+ processor = AutoProcessor.from_pretrained(checkpoint)
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+
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+ device = "cuda" if torch.cuda.is_available() else "cpu"
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+
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+ model_name = "kr-manish/git-base-pokemon" # Replace with your actual username and model name
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+ model = AutoModelForCausalLM.from_pretrained(model_name).to(device)
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+
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+ url = "https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/pokemon.png" # Replace with the URL of your image
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+ image = Image.open(requests.get(url, stream=True).raw)
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+ inputs = processor(images=image, return_tensors="pt").to(device)
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+
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+ generated_ids = model.generate(pixel_values=inputs.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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+ #a pink and purple pokemon character with big eyes
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+
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+ ```
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+
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  # git-base-pokemon
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  This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.