jdh-algo/JoyVASA
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Doron Adler PRO
Norod78
AI & ML interests
Fooling around with Generative machine learning models.
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Lightricks/LTX-Video
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Dref360/vit_pose_playground
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Norod78's activity
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Reacted to
merve's
post with π
3 days ago
Post
1717
π€ transformers pipelines now support vision language models for easy local inference π«°π»
h/t @yonigozlan for shipping this π©π
you can also use inference API to infer hosted vision LMs (via Python, JS and cURL) https://huggingface.co/docs/api-inference/en/tasks/image-text-to-text
h/t @yonigozlan for shipping this π©π
you can also use inference API to infer hosted vision LMs (via Python, JS and cURL) https://huggingface.co/docs/api-inference/en/tasks/image-text-to-text
liked
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Reacted to
jsulz's
post with π₯
3 days ago
Post
2783
When the XetHub crew joined Hugging Face this fall,
@erinys
and I started brainstorming how to share our work to replace Git LFS on the Hub. Uploading and downloading large models and datasets takes precious time. Thatβs where our chunk-based approach comes in.
Instead of versioning files (like Git and Git LFS), we version variable-sized chunks of data. For the Hugging Face community, this means:
β© Only upload the chunks that changed.
π Download just the updates, not the whole file.
π§ We store your file as deduplicated chunks
In our benchmarks, we found that using CDC to store iterative model and dataset version led to transfer speedups of ~2x, but this isnβt just a performance boost. Itβs a rethinking of how we manage models and datasets on the Hub.
We're planning on our new storage backend to the Hub in early 2025 - check out our blog to dive deeper, and let us know: how could this improve your workflows?
https://huggingface.co/blog/from-files-to-chunks
Instead of versioning files (like Git and Git LFS), we version variable-sized chunks of data. For the Hugging Face community, this means:
β© Only upload the chunks that changed.
π Download just the updates, not the whole file.
π§ We store your file as deduplicated chunks
In our benchmarks, we found that using CDC to store iterative model and dataset version led to transfer speedups of ~2x, but this isnβt just a performance boost. Itβs a rethinking of how we manage models and datasets on the Hub.
We're planning on our new storage backend to the Hub in early 2025 - check out our blog to dive deeper, and let us know: how could this improve your workflows?
https://huggingface.co/blog/from-files-to-chunks
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Reacted to
merve's
post with π₯
7 days ago
Post
4719
OmniVision-968M: a new local VLM for edge devices, fast & small but performant
π¨ a new vision language model with 9x less image tokens, super efficient
π aligned with DPO for reducing hallucinations
β‘οΈ Apache 2.0 license π₯
Demo hf.co/spaces/NexaAIDev/omnivlm-dpo-demo
Model NexaAIDev/omnivision-968M
π¨ a new vision language model with 9x less image tokens, super efficient
π aligned with DPO for reducing hallucinations
β‘οΈ Apache 2.0 license π₯
Demo hf.co/spaces/NexaAIDev/omnivlm-dpo-demo
Model NexaAIDev/omnivision-968M
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