| 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 125-million-parameter RoBERTa-Base 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-base") | |
| tokenizer = AutoTokenizer.from_pretrained("valuesimplex-ai-lab/FinBERT2-base") | |
| ``` | |
| ### Further Usage | |
| continual pre-training or fine-tuning：https://github.com/valuesimplex/FinBERT | |