llm-semantic-router/Vela-1.0-Encoder-307M-Domain

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Vela Domain

Vela Domain identifies the subject of a request across 14 domains to help select relevant models and tools.

307M parameters · Input capacity: 32,768 tokens, including special tokens.

Evaluation

Macro F1 (×100) on the same development sets, compared with the original mmBERT32K Domain model. Higher is better.

Evaluation	Original mmBERT	Vela
Short requests · 1,988	66.33	85.15
Controlled 4K context · 28	7.14	71.19
Controlled 8K context · 28	1.79	81.19
Controlled 16K context · 28	1.79	81.19
Controlled 32K context · 28	1.79	77.86

Short requests cover English, Chinese, Spanish, French, German and Japanese. Long-context evaluation uses 28 English/Chinese examples extended to each length. Both models process the complete input in FP32. These development sets informed Vela checkpoint selection; they are not an independent test set.

Quick start

With PyTorch and Transformers 4.57.6 or 5.17.0:

from transformers import pipeline

model_id = "llm-semantic-router/Vela-1.0-Encoder-307M-Domain"
model = pipeline("text-classification", model=model_id, device=-1)
print(model("Why do bond prices fall when interest rates rise?", top_k=None, truncation=False))

Explore the Vela model collection