all-roberta-large-v1
This is a sentence-transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
Params
360 M
Context
512
Downloads 30d
636 K
Likes
66
Download history
daily snapshots · 55 days
▲ 161 K in the last 30 days (20.2%)
750 K636 K
Aug 22Sep 1Sep 11Sep 20
1.1 M636 K
Jul 28Aug 15Sep 2Sep 20
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 | 1.4 GB | 2.1 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
- RobertaForMaskedLM
- Parameters
- 360 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 50,265
- Layers / heads
- 24 / 16
- Licence
- apache-2.0
- First seen on the Hub
- 2022-03-02
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any sentence-similarity model