finbert
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. Financial PhraseBank by Malo et al. (2014) is used for fine-tuning. For more details, please see the paper FinBERT: Financial Sentiment Analysis with Pre-trained Langua...
Params
110 M
Context
512
Downloads 30d
3.3 M
Likes
1,299
Commercial use: not allowed · cc-by-nc-sa-4.0
Not gated
SAFETENSORS
1 languages
View on Hugging Face ↗
Download history
daily snapshots · 106 days
▲ 1.2 M in the last 30 days (26.9%)
4.4 M3.3 M
Oct 12Oct 22Nov 1Nov 10
5.5 M3.3 M
Aug 13Sep 12Oct 12Nov 10
6.5 M3.3 M
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 | 0.4 GB | 1.0 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
- 110 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 30,522
- Layers / heads
- 12 / 12
- Licence
- cc-by-nc-sa-4.0
- First seen on the Hub
- 2022-03-02
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any text-classification model