Sentence Similarity
sentence-transformers
Safetensors
English
Chinese
qwen2
mteb
retriever
text-embeddings-inference
custom_code
Instructions to use Kingsoft-LLM/QZhou-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Kingsoft-LLM/QZhou-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Kingsoft-LLM/QZhou-Embedding", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
update model params
Browse files
model-00002-of-00003.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4932750280
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c1adf7ff241fd393c1cb6ce3f915445c2524eff595d649b272d7950b2083d515
|
| 3 |
size 4932750280
|