gliner2.5-multi-v1
> Extract entities, classify text, parse structured records, score span attributes, and extract relations — all in one boundary architecture.
Params
287 M
Context
—
Downloads 30d
266 K
Likes
274
Download history
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Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 1.1 GB | 1.8 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- BoundaryExtractor
- Parameters
- 287 M
- Tensor type
- F32
- Licence
- apache-2.0
- First seen on the Hub
- 2026-08-14
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-22
Compare with any token-classification model