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
Commit ·
13ee917
1
Parent(s): b455bb0
Update README.md
Browse files
README.md
CHANGED
|
@@ -111,7 +111,7 @@ CoSENT(
|
|
| 111 |
)
|
| 112 |
```
|
| 113 |
## Citing & Authors
|
| 114 |
-
This model was trained by [text2vec
|
| 115 |
|
| 116 |
If you find this model helpful, feel free to cite:
|
| 117 |
```bibtex
|
|
|
|
| 111 |
)
|
| 112 |
```
|
| 113 |
## Citing & Authors
|
| 114 |
+
This model was trained by [text2vec](https://github.com/shibing624/text2vec).
|
| 115 |
|
| 116 |
If you find this model helpful, feel free to cite:
|
| 117 |
```bibtex
|