Instructions to use BorisTM/loss-guided-static-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BorisTM/loss-guided-static-multi with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BorisTM/loss-guided-static-multi") 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 config.json from BorisTM/loss-guided-static-multi: direct link, hf CLI and curl.
- Browser
- Download file 189 Bytes
-
https://huggingface.co/BorisTM/loss-guided-static-multi/resolve/main/config.json
- Command line
-
hf download hf://BorisTM/loss-guided-static-multi/config.json
-
curl -L -o config.json https://huggingface.co/BorisTM/loss-guided-static-multi/resolve/main/config.json
189 Bytes
| { | |
| "embedding_dim": 1024, | |
| "base_vocab_size": 257914, | |
| "pair_rows": 56071, | |
| "language_markers": 1914, | |
| "training_languages": 176, | |
| "pooling": "mean", | |
| "normalize_embeddings": true | |
| } | |