Feature Extraction
sentence-transformers
Safetensors
Chinese
bert
meteorology
domain-adaptive
contrastive-learning
retrieval
embedding
text-embeddings-inference
Instructions to use nmcsitian/bge-meteo-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nmcsitian/bge-meteo-zh with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nmcsitian/bge-meteo-zh") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload 1_Pooling/config.json with huggingface_hub
Verified signature61601c3 -
Upload sentence_bert_config.json with huggingface_hub
Verified signaturefb92c81 -
Upload modules.json with huggingface_hub
Verified signature6a4bf8a
-
Add model.safetensors (1.3GB)
094abb1
-
Upload README.md with huggingface_hub
Verified signature16a7d7e -
Upload README.md with huggingface_hub
Verified signature2ad5db9 -
Upload README.md with huggingface_hub
Verified signature40da8d3 -
Upload vocab.txt with huggingface_hub
Verified signaturef9a576f -
Upload tokenizer_config.json with huggingface_hub
Verified signatured730871 -
Upload tokenizer.json with huggingface_hub
Verified signaturefa41c47 -
Upload special_tokens_map.json with huggingface_hub
Verified signature6328ddb -
Upload config.json with huggingface_hub
Verified signaturec135ab1 -
Upload README.md with huggingface_hub
Verified signaturea1fd711 -
initial commit
Verified signaturecfa2256