Feature Extraction
sentence-transformers
PyTorch
English
distilbert
splade
query-expansion
document-expansion
bag-of-words
passage-retrieval
knowledge-distillation
sparse-encoder
sparse
Instructions to use naver/splade_v2_distil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/splade_v2_distil with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("naver/splade_v2_distil") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "name_or_path": "distilbert-base-uncased"} |