Sentence Similarity
sentence-transformers
PyTorch
ONNX
xlm-roberta
feature-extraction
Eval Results
text-embeddings-inference
Instructions to use BAAI/bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/bge-m3") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
入参之间会影响embedding的结果吗
#22
by biaodiluer - opened
不管后面跟了什么字符串,"hello word, bob"的embedding结果不应该是固定的吗(我试了openai是固定的) -。-
推理多个文本时,由于padding,fp16等因素,结果可能与单个推理存在差异。从图中的结果来看,属于正常范围,这个差异很小,对排序结果没有影响。

