Text Classification
Transformers
ONNX
Safetensors
modernbert
semantic-router
vela
text-embeddings-inference
Instructions to use vllm-sr/Vela-1.0-Encoder-307M-Modality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/Vela-1.0-Encoder-307M-Modality with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vllm-sr/Vela-1.0-Encoder-307M-Modality")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vllm-sr/Vela-1.0-Encoder-307M-Modality") model = AutoModelForSequenceClassification.from_pretrained("vllm-sr/Vela-1.0-Encoder-307M-Modality", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
19 days ago
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Update Hugging Face org references: llm-semantic-router → vllm-sr
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Add portable FP32 ONNX inference
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Add original mmBERT evaluation comparison for Vela Modality
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Simplify Vela quick starts and model cards
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Release Vela on the unified Encoder base
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Unify Vela model cards with Semantic Router branding
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Add Vela Embedding to the model family
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Add Vela Feedback to the model family
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Add Vela Reranker to the model family
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Introduce the Vela model family and simplify the model card
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Release Vela-1.0-Encoder-307M-Modality with frozen task and native engine evidence
Verified signatureNew text-model release with immutable task weights, original-parent lineage where retained, independent final evaluation, source-pinned training reproduction, frozen LoRA, and FP32 ONNX GPU qualification through 32K. Model card reports source, class and long-context limitations; existing repositories remain unchanged.f4ee346 -
initial commit
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