Sentence Similarity
sentence-transformers
PyTorch
Chinese
bert
feature-extraction
text-embeddings-inference
Instructions to use oldhu/text2vec-lert-base-5-tasks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use oldhu/text2vec-lert-base-5-tasks with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("oldhu/text2vec-lert-base-5-tasks") 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 1_Pooling/config.json from oldhu/text2vec-lert-base-5-tasks: direct link, hf CLI and curl.
- Browser
- Download file 74 Bytes
-
https://huggingface.co/oldhu/text2vec-lert-base-5-tasks/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://oldhu/text2vec-lert-base-5-tasks/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/oldhu/text2vec-lert-base-5-tasks/resolve/main/1_Pooling/config.json
74 Bytes
| { | |
| "word_embedding_dimension": 768, | |
| "pooling_mode_mean_tokens": true | |
| } | |