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Juan Pablo Gallego
jpgallegoar
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Let's go! We are releasing SmolVLM, a smol 2B VLM built for on-device inference that outperforms all models at similar GPU RAM usage and tokens throughputs. - SmolVLM generates tokens 7.5 to 16 times faster than Qwen2-VL! 🤯 - Other models at this size crash a laptop, but SmolVLM comfortably generates 17 tokens/sec on a macbook! 🚀 - SmolVLM can be fine-tuned on a Google collab! Or process millions of documents with a consumer GPU! - SmolVLM even outperforms larger models in video benchmarks, despite not even being trained on videos! Check out more! Demo: https://huggingface.co/spaces/HuggingFaceTB/SmolVLM Blog: https://huggingface.co/blog/smolvlm Model: https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct Fine-tuning script: https://github.com/huggingface/smollm/blob/main/finetuning/Smol_VLM_FT.ipynb
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Spanish F5
Spanish finetune for the original F5 model.
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jpgallegoar/F5-Spanish
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7 days ago
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