|
|
--- |
|
|
license: apache-2.0 |
|
|
language: |
|
|
- zh |
|
|
base_model: |
|
|
- hfl/chinese-roberta-wwm-ext |
|
|
tags: |
|
|
- finance |
|
|
--- |
|
|
|
|
|
## Model Details |
|
|
|
|
|
**Model Description:** This is a finance-domain pretrained Chinese language model, which is based on the 355-million-parameter RoBERTa-Large and further pre-trained on 32B tokens of Chinese financial corpora (including a large number of research reports, news, and announcements). |
|
|
|
|
|
- **Developed by:** See [valuesimplex](https://github.com/valuesimplex) for model developers |
|
|
- **Model Type:** Transformer-based language model |
|
|
- **Language(s):** Chinese |
|
|
- **Parent Model:** See the [chinese-roberta](https://huggingface.co/hfl/chinese-roberta-wwm-ext) for more information about the BERT base model. |
|
|
- **Resources for more information:** |
|
|
- [Research Paper](https://dl.acm.org/doi/10.1145/3711896.3737219) |
|
|
- [GitHub Repo](https://github.com/valuesimplex/FinBERT) |
|
|
|
|
|
## Direct Use |
|
|
|
|
|
```python |
|
|
from transformers import AutoModel, AutoTokenizer |
|
|
|
|
|
model = AutoModel.from_pretrained("valuesimplex-ai-lab/FinBERT2-large") |
|
|
tokenizer = AutoTokenizer.from_pretrained("valuesimplex-ai-lab/FinBERT2-large") |
|
|
``` |
|
|
|
|
|
### Further Usage |
|
|
continual pre-training or fine-tuning：https://github.com/valuesimplex/FinBERT |
|
|
|
|
|
|
|
|
|
