Update README.md

README.md

@@ -7,7 +7,29 @@ base_model:
 tags:
 - finance
 ---
-基于3.55亿参数RoBERTa-Large 在32B tokens 金融语料（包含大量研报，新闻，公告）上继续预训练的Chinese FinBERT.
 
-README of continue pre-training and fine-tuning： https://github.com/valuesimplex/FinBERT
+## 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
+