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
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,18 +1,14 @@
|
|
| 1 |
---
|
| 2 |
-
pipeline_tag: sentence-similarity
|
| 3 |
license: apache-2.0
|
|
|
|
| 4 |
tags:
|
| 5 |
-
-
|
| 6 |
- feature-extraction
|
| 7 |
- sentence-similarity
|
| 8 |
-
- transformers
|
| 9 |
datasets:
|
| 10 |
- shibing624/nli_zh
|
| 11 |
language:
|
| 12 |
- zh
|
| 13 |
-
metrics:
|
| 14 |
-
- spearmanr
|
| 15 |
-
library_name: transformers
|
| 16 |
---
|
| 17 |
# shibing624/text2vec-base-chinese
|
| 18 |
This is a CoSENT(Cosine Sentence) model: shibing624/text2vec-base-chinese.
|
|
|
|
| 1 |
---
|
|
|
|
| 2 |
license: apache-2.0
|
| 3 |
+
pipeline_tag: sentence-similarity
|
| 4 |
tags:
|
| 5 |
+
- sentence-transformers
|
| 6 |
- feature-extraction
|
| 7 |
- sentence-similarity
|
|
|
|
| 8 |
datasets:
|
| 9 |
- shibing624/nli_zh
|
| 10 |
language:
|
| 11 |
- zh
|
|
|
|
|
|
|
|
|
|
| 12 |
---
|
| 13 |
# shibing624/text2vec-base-chinese
|
| 14 |
This is a CoSENT(Cosine Sentence) model: shibing624/text2vec-base-chinese.
|