Commit History

  1. Card: note the integration files are on the kw-preview branch too

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  2. Model card: add Sentence Transformers usage section

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  3. Add Sentence Transformers integration (custom module)

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  1. Evaluation integrity: report Common Voice under the training_datasets disclosure; remove internal notes

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  2. Add the evaluation-integrity section (Common Voice overlap disclosure)

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  1. Add self-hosted serving section (vLLM and SGLang plugins)

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  2. Cite the corpus paper (arXiv:2608.01560) at the emotion-regression note it explains

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  1. Add Tactus (touch sense pack) to the model family listing

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  1. Install fusion-embedding from PyPI

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  2. Add Engram playground link

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  3. Add Engram ecosystem section

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  1. Card: clean rebuild - single-row badges + RunPod on next row, fixed frontmatter

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  2. Card: badges on one row, Deploy on RunPod on next row (centered)

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  3. Card: fix line endings (clean LF; restore YAML frontmatter parsing)

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  4. Card: revert to dynamic RunPod badge

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  5. Card: static Deploy on RunPod badge (always renders)

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  6. Card: restore banner, add RunPod deploy

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  7. Card: add RunPod deploy section

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  8. Card: add RunPod Hub deploy badge + endpoint call instructions

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  1. Add v0.3 banner to model card

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  1. v0.3-preview: retrieval-tuned flagship⁠

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  1. Card: separate model citation (Tonmoy) from paper citation (all authors)

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  2. Cite the arXiv paper (2607.18666)

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  1. card: link the Ember thermal sense pack

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  2. Card: MAEB nine-task section with the v0.2 rescore⁠

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  3. config.json: restore the remote-code loading schema⁠

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  4. v0.2: fine-tune on the expanded AudioCaps 2.0 pool (86,394 pairs, 1,600 steps)⁠

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  1. inference.py: native video preprocessing (no qwen-vl-utils)

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  2. embed_video: native preprocessing (frame tensors and torchcodec path decode); drops the qwen-vl-utils dependency; bitwise-equal to the previous implementation and the raw base on identical inputs

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  3. inference.py: embed_video (base's own video path, gate-guarded)

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  4. Add embed_video: the frozen base's own video path (qwen-vl-utils preprocessing, official defaults), gate-guarded like images; bitwise-verified against the base and the reference loader

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  1. Card: AudioCaps T2A R@1 predecessor cell now recorded (0.280)

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  2. Card: positioning alt text matches the trained-parameters axis

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  3. Positioning figure: trained-parameters axis (matches the technical report)

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  4. inference.py: install URL points at the renamed family repo

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  5. Card: code links to the renamed family repo (Eximius-Labs/fusion-embedding); Clotho T2A R@1 predecessor cell now recorded (0.136)

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  6. AutoModel + trust_remote_code support (remote-code loading; existing loaders unchanged)

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  7. Card: precise cell count (8 of 12 release-protocol cells; every recorded text-to-audio direction)

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  8. inference.py: gate guard on embed_image (non-audio inputs must run with the gate closed)

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  9. model card: positioning chart visible in Evaluation

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  10. assets: positioning chart — distinct hues for the two generations

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  11. model card: positioning chart in cross-modal section

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  12. assets: unified-model positioning chart

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  13. assets: overview figure from the unified family generator

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  14. assets: overview figure in Eximius Labs palette

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  15. assets: overview figure — EOS chip inside pooling box

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  16. assets: overview figure — horizontal pooling arrow

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  17. assets: model overview figure v2 (layer-stack style)

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  18. model card: add model overview figure

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  19. assets: model overview figure

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