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

liuyanyi/bge-m3-hf

BGE-M3 in HuggingFace Transformer

Introduction

Use BGE-M3 in HuggingFace Transformer

References

liuyanyi/
bge-m3-hf