Total runs:
32.7K
Run Growth:
-2.6K
Growth Rate:
-8.04%
Sponsored by
PoYo.AI
llm-semantic-router / Vela-1.0-Encoder-307M
Model's Last Updated: September 13 2026
fill-mask
Introduction of Vela-1.0-Encoder-307M
Model Details of Vela-1.0-Encoder-307M
Vela Base
Vela Base is a multilingual encoder foundation for specialized routing models.
307M parameters · Input capacity: 32,768 tokens, including special tokens.
Evaluation
Masked-token negative log-likelihood on the same multilingual development set, compared with the original mmBERT32K Base . Lower is better.
| Context length | Original mmBERT | Vela |
|---|---|---|
| 512 tokens · 156 windows | 1.441 | 1.387 |
| 8K tokens · 54 windows | 1.226 | 1.212 |
| 16K tokens · 54 windows | 1.206 | 1.168 |
| 32K tokens · 54 windows | 1.075 | 1.018 |
The 318 windows cover English, Chinese, German, French, Japanese and Arabic. Both models use FP32, identical fixed 15% masked-token targets, and complete inputs without truncation. This development set informed Vela checkpoint selection; it is 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"
model = pipeline("fill-mask", model=model_id, device=-1)
print(model(f"The capital of France is {model.tokenizer.mask_token}."))
Runs of llm-semantic-router Vela-1.0-Encoder-307M on huggingface.co
1.2K
Total runs
0
24-hour runs
37
3-day runs
428
7-day runs
596
30-day runs
More Information About Vela-1.0-Encoder-307M huggingface.co Model
Url of Vela-1.0-Encoder-307M
Vela-1.0-Encoder-307M huggingface.co Url
Provider of Vela-1.0-Encoder-307M huggingface.co
Other API from llm-semantic-router
Updated:March 06 2026
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