Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bert
mteb
feature-extraction
Eval Results (legacy)
text-embeddings-inference
Instructions to use aspire/acge_text_embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use aspire/acge_text_embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aspire/acge_text_embedding") 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
关于训练代码
#4
by PatrickStar1 - opened
不知道大佬的训练代码是否开源?想学习一下
aspire changed discussion status to closed
请教下 matryoshka 在训练期间用了哪些维度?
我使用的是[512, 768, 1024, 1536, 1792],权重也都是[1, 1, 1, 1, 1],这个并没有做大量的实践,如果有更好的维度方式,也可以互相交流。
aspire changed discussion status to open
我使用的是[512, 768, 1024, 1536, 1792],权重也都是[1, 1, 1, 1, 1],这个并没有做大量的实践,如果有更好的维度方式,也可以互相交流。
请问使用matryoshka能提升模型效果吗?