Sentence Similarity
Transformers
Safetensors
sentence-transformers
Chinese
utu
feature-extraction
text-embeddings-inference
custom_code
Instructions to use tencent/Youtu-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/Youtu-Embedding with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tencent/Youtu-Embedding", trust_remote_code=True, dtype="auto") - sentence-transformers
How to use tencent/Youtu-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tencent/Youtu-Embedding", trust_remote_code=True) 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
Update (#5)
Browse files- Update (2c12edbb0e60ae4d195871d9d527a19214932270)
README.md
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
---
|
| 2 |
-
license:
|
| 3 |
language:
|
| 4 |
- zh
|
| 5 |
pipeline_tag: sentence-similarity
|
|
@@ -10,6 +10,7 @@ tags:
|
|
| 10 |
- sentence-similarity
|
| 11 |
- feature-extraction
|
| 12 |
- text-embeddings-inference
|
|
|
|
| 13 |
---
|
| 14 |
<p align="center">
|
| 15 |
<img src="images/youtu_embedding.png" width="400"/>
|
|
|
|
| 1 |
---
|
| 2 |
+
license: mit
|
| 3 |
language:
|
| 4 |
- zh
|
| 5 |
pipeline_tag: sentence-similarity
|
|
|
|
| 10 |
- sentence-similarity
|
| 11 |
- feature-extraction
|
| 12 |
- text-embeddings-inference
|
| 13 |
+
extra_gated_eu_disallowed: true
|
| 14 |
---
|
| 15 |
<p align="center">
|
| 16 |
<img src="images/youtu_embedding.png" width="400"/>
|