| --- |
| 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 |
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