Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
Chinese
bert
Sentence Transformers
Instructions to use shibing624/text2vec-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shibing624/text2vec-base-chinese with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shibing624/text2vec-base-chinese") sentences = [ "那是 個快樂的人", "那是 條快樂的狗", "那是 個非常幸福的人", "今天是晴天" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
模型最大支持的Token数
#11
by jeffersonchou - opened
请问模型最大支持的Token数是多少?如果max_seq_length是128个Token?是否近似于128个汉字?
是
shibing624 changed discussion status to closed
是
max_seq_length 是128,如何增大这个数,来增加输入长度?
重新用长的训练集训练就可以。