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VisionEncoder

Transformers
Safetensors
vision-encoder
distillation
video-language
siglip2
dinov3
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VisionEncoder

Commit History

  1. Upload V13.6 S2 checkpoint

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  2. Upload V13.5 S2 checkpoint

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  3. Upload V13.3 S2 checkpoint

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  4. Upload V13.2 S2 checkpoint

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  5. Upload V13.1 S2 checkpoint

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  6. Upload V13.0 S2 checkpoint

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  1. Add V12.4.6 video decode manifest

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  1. chore: remove S0 placeholder

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  2. upload V10.2 S0 main weights

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  3. chore: add S0 checkpoint directory

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  1. rename ckpts stock_{16f,32f}_10pct -> baseline_* (naming consistency)

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  1. add V10.x cache vjepa21/video_10pct_chunks

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  2. add V10.x cache qwen3vit/video_10pct_64f

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  3. add V10.x cache qwen3vit/video_10pct_32f

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  4. add V10.x cache vjepa21/image_10pct

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  1. Cleanup: remove flat 4b_stock/4b_v9_1 (moved into S2) + mistaken flat 32f dirs

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  2. Reorg: move 16f stock/v9_1 ckpts into S2 stage-first tree (drop machine name, tag 16f)

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  3. Reorg: flatten 32f ckpts to ckpts/{v10_2_32f,stock_32f}

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  4. Add 4B 32f inference ckpt under stage-first ckpts/ -> ckpts/S2/4b/qwen3_5_2b/stock_32f_10pct/v0-20260606-044138/checkpoint-785

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  5. Add 4B 32f inference ckpt under stage-first ckpts/ -> ckpts/S2/4b/qwen3_5_2b/v10_2_32f_10pct/v0-20260610-154054/checkpoint-785

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  6. remove write-path test marker

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  7. write-path test marker

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  1. docs: fix eval pointer (GitHub README step 7 -> section 4)

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  2. Update model card for data/ + ckpts/ + legacy/ restructure

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  3. Remove ckpts placeholder now that real ckpts landed

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  4. Add 4B MLLM ckpt: 4b_v9_1 (checkpoint-505, inference weights)

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  5. Add 4B MLLM ckpt: 4b_stock (checkpoint-505, inference weights)

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  6. Create ckpts/ folder for current trained checkpoints

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  7. Restructure repo into data/ + legacy/ (batch 14)

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  8. Restructure repo into data/ + legacy/ (batch 13)

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  9. Restructure repo into data/ + legacy/ (batch 12)

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  10. Restructure repo into data/ + legacy/ (batch 11)

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  11. Restructure repo into data/ + legacy/ (batch 10)

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  12. Restructure repo into data/ + legacy/ (batch 9)

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  13. Restructure repo into data/ + legacy/ (batch 8)

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  14. Restructure repo into data/ + legacy/ (batch 7)

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  15. Restructure repo into data/ + legacy/ (batch 6)

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  16. Restructure repo into data/ + legacy/ (batch 5)

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  17. Restructure repo into data/ + legacy/ (batch 4)

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  18. Restructure repo into data/ + legacy/ (batch 3)

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  19. Restructure repo into data/ + legacy/ (batch 2)

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  20. Restructure repo into data/ + legacy/ (batch 1)

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  21. Add V9 good_manifest (decode-probed video list) for collaborator repro

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  1. Add vmllm_cached cached datasets (6.2G, 693 files)

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  1. docs: add README describing checkpoint layout and training code mapping

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  1. Upload folder using huggingface_hub

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  2. Upload folder using huggingface_hub

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  3. Upload folder using huggingface_hub

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  4. Upload folder using huggingface_hub

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  5. Upload folder using huggingface_hub

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