Create README.md

README.md

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+---
+pipeline_tag: sentence-similarity
+tags:
+  - sentence-transformers
+  - feature-extraction
+  - sentence-similarity
+---
+# BGE-M3 in HuggingFace Transformer
+
+> **This is not an official implementation of BGE-M3. Official implementation can be found in [Flag Embedding](https://github.com/FlagOpen/FlagEmbedding) project.**
+
+## Introduction
+
+Full introduction please see the github repo.
+
+https://github.com/liuyanyi/transformers-bge-m3
+
+## Use BGE-M3 in HuggingFace Transformer
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+# Trust remote code is required to load the model
+tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+model = AutoModel.from_pretrained(model_path, trust_remote_code=True)
+
+input_str = "Hello, world!"
+input_ids = tokenizer(input_str, return_tensors="pt", padding=True, truncation=True)
+
+output = model(**input_ids, return_dict=True)
+
+dense_output = output.dense_output # To align with Flag Embedding project, a normalization is required
+colbert_output = output.colbert_output # To align with Flag Embedding project, a normalization is required
+sparse_output = output.sparse_output
+```
+
+## References
+
+- [Official BGE-M3 Weight](https://huggingface.co/BAAI/bge-m3)
+- [Flag Embedding](https://github.com/FlagOpen/FlagEmbedding)
+- [HuggingFace Transformer](https://github.com/huggingface/transformers)