Create README.md

README.md

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+---
+language:
+- en
+pipeline_tag: feature-extraction
+tags:
+- pytorch
+- RoBERTa
+---
+# Model Card for SynCSE-scratch  
+ 
+# Model Details
+ 
+## Model Description
+ 
+More information needed
+ 
+- **Developed by:** SJTU-LIT
+- **Shared by [Optional]:** SJTU-LIT
+
+- **Model type:** Feature Extraction
+- **Language(s) (NLP):** More information needed
+- **License:** More information needed
+- **Parent Model:** RoBERTa-base
+- **Resources for more information:**
+ 	 - [GitHub Repo](https://github.com/SJTU-LIT/SynCSE/tree/main)
+ 	 - [Associated Paper](https://arxiv.org/abs/2305.15077)
+
+
+# Uses
+ 
+
+## Direct Use
+This model can be used for the task of feature extraction. 
+ 
+## Out-of-Scope Use
+ 
+The model should not be used to intentionally create hostile or alienating environments for people. 
+ 
+# Bias, Risks, and Limitations
+ 
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
+## Recommendations
+ 
+ 
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+
+ 
+# Training Data
+ 
+  The model craters note in the [Github Repository](https://github.com/SJTU-LIT/SynCSE/blob/main/README.md)
+> We use 27.5k generated synthetic train SynCSE-sractch-RoBERTa-base.
+ 
+# Citation
+
+ 
+**BibTeX:**
+
+```bibtex
+@article{zhang2023contrastive,
+  title={Contrastive Learning of Sentence Embeddings from Scratch},
+  author={Zhang, Junlei and Lan, Zhenzhong and He, Junxian},
+  journal={arXiv preprint arXiv:2305.15077},
+  year={2023}
+}
+```
+
+# Model Card Contact
+ 
+If you have any questions related to the code or the paper, feel free to email Junlei (`zhangjunlei@westlake.edu.cn`). If you encounter any problems when using the code, or want to report a bug, you can open an issue. Please try to specify the problem with details so we can help you better and quicker!
+
+
+ 
+# How to Get Started with the Model
+ 
+Use the code below to get started with the model.
+ 
+<details>
+<summary> Click to expand </summary>
+
+```python
+from transformers import AutoTokenizer, AutoModel
+tokenizer = AutoTokenizer.from_pretrained("sjtu-lit/SynCSE-partial-RoBERTa-base")
+model = AutoModel.from_pretrained("sjtu-lit/SynCSE-partial-RoBERTa-base")
+ 
+ ```
+</details>