Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
Chinese
bert
Sentence Transformers
Instructions to use ChenZ95/text2vec-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ChenZ95/text2vec-base-chinese with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ChenZ95/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] - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ChenZ95/text2vec-base-chinese: direct link, hf CLI and curl.
- Browser
- Download file 319 Bytes
-
https://huggingface.co/ChenZ95/text2vec-base-chinese/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ChenZ95/text2vec-base-chinese/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ChenZ95/text2vec-base-chinese/resolve/main/tokenizer_config.json
319 Bytes
| {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "name_or_path": "hfl/chinese-macbert-base", "tokenizer_class": "BertTokenizer"} | |