OpenMed-NER-PharmaDetect-BigMed-278M
Specialized model for Chemical Entity Recognition - Chemical entities from the BC5CDR dataset
Params
278 M
Context
512
Downloads 30d
219 K
Likes
6
Download history
daily snapshots · 52 days
▲ 3 K in the last 30 days (1.5%)
223 K209 K
Oct 12Oct 22Nov 1Nov 10
225 K209 K
Sep 20Oct 7Oct 24Nov 10
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 | bf16 | 0.6 GB | 1.2 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
- XLMRobertaForTokenClassification
- Parameters
- 278 M
- Tensor type
- BF16
- Context length
- 512
- Vocabulary
- 250,002
- Layers / heads
- 12 / 12
- Licence
- apache-2.0
- First seen on the Hub
- 2025-07-16
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-20
Compare with any token-classification model