Feature Extraction
sentence-transformers
Safetensors
English
fusion-embedding-connector
embeddings
multimodal
audio
retrieval
matryoshka
qwen3-vl
adapters
custom_code
Instructions to use EximiusLabs/fusion-embedding-2-2b-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use EximiusLabs/fusion-embedding-2-2b-preview with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("EximiusLabs/fusion-embedding-2-2b-preview", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Commit History
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Card: note the integration files are on the kw-preview branch too
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Model card: add Sentence Transformers usage section
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Add Sentence Transformers integration (custom module)
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Evaluation integrity: report Common Voice under the training_datasets disclosure; remove internal notes
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Add the evaluation-integrity section (Common Voice overlap disclosure)
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Add self-hosted serving section (vLLM and SGLang plugins)
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Cite the corpus paper (arXiv:2608.01560) at the emotion-regression note it explains
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Add Tactus (touch sense pack) to the model family listing
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Install fusion-embedding from PyPI
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Add Engram playground link
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Add Engram ecosystem section
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Card: clean rebuild - single-row badges + RunPod on next row, fixed frontmatter
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Card: badges on one row, Deploy on RunPod on next row (centered)
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Card: fix line endings (clean LF; restore YAML frontmatter parsing)
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Card: revert to dynamic RunPod badge
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Card: static Deploy on RunPod badge (always renders)
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Card: restore banner, add RunPod deploy
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Card: add RunPod deploy section
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Card: add RunPod Hub deploy badge + endpoint call instructions
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Add v0.3 banner to model card
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v0.3-preview: retrieval-tuned flagship
Verified signatureAudioCaps a2t R@10 0.743 -> 0.785 over v0.2; t2a R@10 0.782. MAEB(audio-only) 19-task mean 0.454; leads IEMOCAP speaker-gender (0.938). RAVDESS zero-shot emotion regressed to 0.21. Non-audio (text/image/video) outputs remain bit-for-bit the frozen base model's, verified on this artifact before push. Ships a second keyword-tuned revision on branch v0.3-kw-preview.1720d8b
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Card: separate model citation (Tonmoy) from paper citation (all authors)
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Cite the arXiv paper (2607.18666)
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card: link the Ember thermal sense pack
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Card: MAEB nine-task section with the v0.2 rescore
Verified signaturev0.2 evaluated at revision 9451b840f0d1 (mteb 2.18.x, identical protocol to the v0.1 submission): mean .361 vs .354, six of nine tasks improved.eeb829b -
config.json: restore the remote-code loading schema
Verified signatureThe v0.2 weights commit replaced config.json with the packager payload, dropping auto_map/architectures and the model-construction fields the trust_remote_code path requires. Restored from the previous revision with the v0.2 benchmark payload merged in.9451b84 -
v0.2: fine-tune on the expanded AudioCaps 2.0 pool (86,394 pairs, 1,600 steps)
Verified signatureAudioCaps A2T R@10 0.743 -> 0.759, T2A R@10 0.775 -> 0.785; Clotho and VGGSound audio-text within noise of v0.1 under paired protocols; emergent audio-image up ~1.5 points. Non-audio outputs remain bit-for-bit the base model's (verified on this artifact before push). Card updated accordingly.35d1d2f
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inference.py: native video preprocessing (no qwen-vl-utils)
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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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inference.py: embed_video (base's own video path, gate-guarded)
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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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Card: AudioCaps T2A R@1 predecessor cell now recorded (0.280)
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Card: positioning alt text matches the trained-parameters axis
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Positioning figure: trained-parameters axis (matches the technical report)
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inference.py: install URL points at the renamed family repo
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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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AutoModel + trust_remote_code support (remote-code loading; existing loaders unchanged)
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Card: precise cell count (8 of 12 release-protocol cells; every recorded text-to-audio direction)
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inference.py: gate guard on embed_image (non-audio inputs must run with the gate closed)
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model card: positioning chart visible in Evaluation
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assets: positioning chart — distinct hues for the two generations
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model card: positioning chart in cross-modal section
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assets: unified-model positioning chart
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assets: overview figure from the unified family generator
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assets: overview figure in Eximius Labs palette
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assets: overview figure — EOS chip inside pooling box
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assets: overview figure — horizontal pooling arrow
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assets: model overview figure v2 (layer-stack style)
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model card: add model overview figure
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assets: model overview figure
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