bert-base-multilingual-uncased-sentiment
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Params
170 M
Context
512
Downloads 30d
571 K
Likes
497
Download history
daily snapshots · 106 days
▲ 121 K in the last 30 days (17.6%)
711 K571 K
Oct 12Oct 22Nov 1Nov 10
923 K571 K
Aug 13Sep 12Oct 12Nov 10
923 K571 K
Jul 28Sep 1Oct 6Nov 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 | f32 | 0.7 GB | 1.3 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
- BertForSequenceClassification
- Parameters
- 170 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 105,879
- Layers / heads
- 12 / 12
- Licence
- mit
- First seen on the Hub
- 2022-03-02
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any text-classification model