Feature Extraction
sentence-transformers
Safetensors
French
modernbert
splade
sparse
retrieval
sentence-similarity
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use alphaedge-ai/sparseup-fr-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/sparseup-fr-v0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/sparseup-fr-v0") 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 1_SparseUpPooling/config.json from alphaedge-ai/sparseup-fr-v0: direct link, hf CLI and curl.
- Browser
- Download file 379 Bytes
-
https://huggingface.co/alphaedge-ai/sparseup-fr-v0/resolve/main/1_SparseUpPooling/config.json
- Command line
-
hf download hf://alphaedge-ai/sparseup-fr-v0/1_SparseUpPooling/config.json
-
curl -L -o config.json https://huggingface.co/alphaedge-ai/sparseup-fr-v0/resolve/main/1_SparseUpPooling/config.json
379 Bytes
| { | |
| "logit_shift": 2.0, | |
| "position_top_k": 12, | |
| "vocab_fold": "case_space", | |
| "chunk_size": 32, | |
| "prefix_token_ids": [ | |
| [ | |
| 50238 | |
| ], | |
| [ | |
| 50239 | |
| ] | |
| ], | |
| "special_token_ids": [ | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 50238, | |
| 50239 | |
| ], | |
| "embedding_dimension": 50240, | |
| "pool_factor": 1 | |
| } |