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Vela Modality

Vela Modality identifies whether a request needs text output (AR), image generation (DIFFUSION), or both (BOTH).

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

Evaluation

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

Evaluation	Original mmBERT	Vela
Short inputs · 929	38.40	81.10
Controlled 4K context · 18	26.67	82.22
Controlled 8K context · 18	26.67	82.22
Controlled 16K context · 18	26.67	82.22
Controlled 32K context · 18	26.67	82.22

Short inputs cover six languages. Long-context evaluation uses six English/Chinese examples placed at three positions and repeated across lengths. Both models process complete inputs in FP32. These development sets informed Vela 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-Modality"
model = pipeline("text-classification", model=model_id, device=-1)
print(model("Create a watercolor image of a lighthouse at sunset.", top_k=None, truncation=False))

Explore the Vela model collection