Instructions to use uer/sbert-base-chinese-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use uer/sbert-base-chinese-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("uer/sbert-base-chinese-nli") sentences = [ "那个人很开心", "那个人非常开心", "那只猫很开心", "那个人在吃东西" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use uer/sbert-base-chinese-nli with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("uer/sbert-base-chinese-nli") model = AutoModel.from_pretrained("uer/sbert-base-chinese-nli") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#6 opened about 2 years ago
by
SFconvertbot
To solve the warning from sentence_transformers, add 4 configs files.
2
#3 opened over 3 years ago
by
pe65374
使用hf推荐的语句引用的时候,发生"No sentence-transformers model found..." feedback
5
#2 opened over 3 years ago
by
pe65374
Can not reproduce the model
#1 opened almost 4 years ago
by
ningyuan