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@@ -12,7 +12,7 @@ pipeline_tag: visual-question-answering
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  ## Model Description
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- **paligemma-3b-tablevqa-896-lora** is a fine-tuned version of the **[google/paligemma-3b-ft-docvqa-896](https://huggingface.co/google/paligemma-3b-ft-docvqa-896)** model,
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  trained specifically on the **[table-vqa](https://huggingface.co/datasets/cmarkea/table-vqa)** dataset published by Crédit Mutuel Arkéa. This model leverages the
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  **LoRA** (Low-Rank Adaptation) technique, which significantly reduces the computational complexity of fine-tuning while maintaining high performance. The model operates
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  in bfloat16 precision for efficiency, making it an ideal solution for resource-constrained environments.
@@ -47,7 +47,7 @@ import requests
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  import torch
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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- model_id = "cmarkea/paligemma-tablevqa-896-lora"
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  # Sample image for inference
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  url = "https://datasets-server.huggingface.co/cached-assets/cmarkea/table-vqa/--/c26968da3346f92ab6bfc5fec85592f8250e23f5/--/default/train/22/image/image.jpg?Expires=1728915081&Signature=Zkrd9ZWt5b9XtY0UFrgfrTuqo58DHWIJ00ZwXAymmL-mrwqnWWmiwUPelYOOjPZZdlP7gAvt96M1PKeg9a2TFm7hDrnnRAEO~W89li~AKU2apA81M6AZgwMCxc2A0xBe6rnCPQumiCGD7IsFnFVwcxkgMQXyNEL7bEem6cT0Cief9DkURUDCC-kheQY1hhkiqLLUt3ITs6o2KwPdW97EAQ0~VBK1cERgABKXnzPfAImnvjw7L-5ZXCcMJLrvuxwgOQ~DYPs456ZVxQLbTxuDwlxvNbpSKoqoAQv0CskuQwTFCq2b5MOkCCp9zoqYJxhUhJ-aI3lhyIAjmnsL4bhe6A__&Key-Pair-Id=K3EI6M078Z3AC3"
 
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  ## Model Description
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+ **paligemma-3b-ft-tablevqa-896-lora** is a fine-tuned version of the **[google/paligemma-3b-ft-docvqa-896](https://huggingface.co/google/paligemma-3b-ft-docvqa-896)** model,
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  trained specifically on the **[table-vqa](https://huggingface.co/datasets/cmarkea/table-vqa)** dataset published by Crédit Mutuel Arkéa. This model leverages the
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  **LoRA** (Low-Rank Adaptation) technique, which significantly reduces the computational complexity of fine-tuning while maintaining high performance. The model operates
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  in bfloat16 precision for efficiency, making it an ideal solution for resource-constrained environments.
 
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  import torch
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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+ model_id = "cmarkea/paligemma-3b-ft-tablevqa-896-lora"
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  # Sample image for inference
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  url = "https://datasets-server.huggingface.co/cached-assets/cmarkea/table-vqa/--/c26968da3346f92ab6bfc5fec85592f8250e23f5/--/default/train/22/image/image.jpg?Expires=1728915081&Signature=Zkrd9ZWt5b9XtY0UFrgfrTuqo58DHWIJ00ZwXAymmL-mrwqnWWmiwUPelYOOjPZZdlP7gAvt96M1PKeg9a2TFm7hDrnnRAEO~W89li~AKU2apA81M6AZgwMCxc2A0xBe6rnCPQumiCGD7IsFnFVwcxkgMQXyNEL7bEem6cT0Cief9DkURUDCC-kheQY1hhkiqLLUt3ITs6o2KwPdW97EAQ0~VBK1cERgABKXnzPfAImnvjw7L-5ZXCcMJLrvuxwgOQ~DYPs456ZVxQLbTxuDwlxvNbpSKoqoAQv0CskuQwTFCq2b5MOkCCp9zoqYJxhUhJ-aI3lhyIAjmnsL4bhe6A__&Key-Pair-Id=K3EI6M078Z3AC3"