Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use GreenNode/GreenNode-Embedding-Large-1007 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GreenNode/GreenNode-Embedding-Large-1007 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GreenNode/GreenNode-Embedding-Large-1007") 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
Download sparse_linear.pt from GreenNode/GreenNode-Embedding-Large-1007: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/GreenNode/GreenNode-Embedding-Large-1007/resolve/main/sparse_linear.pt
- Command line
-
hf download hf://GreenNode/GreenNode-Embedding-Large-1007/sparse_linear.pt
-
curl -L -o sparse_linear.pt https://huggingface.co/GreenNode/GreenNode-Embedding-Large-1007/resolve/main/sparse_linear.pt
5.56 kB
- Xet hash:
- 80a61ac1e8f6375bb7b1eb0b622d274e07e6a943eaa832663677bd616ffd0dbd
- Size of remote file:
- 5.56 kB
- SHA256:
- f2ac2ac28528d8c2063ec62af1705e49ec0f75a89dc52ffce67f4aa17d4770e3
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