Feature Extraction
sentence-transformers
PyTorch
Safetensors
English
distilbert
splade
query-expansion
document-expansion
bag-of-words
passage-retrieval
knowledge-distillation
document encoder
sparse-encoder
sparse
asymmetric
text-embeddings-inference
Instructions to use naver/efficient-splade-V-large-query with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/efficient-splade-V-large-query with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("naver/efficient-splade-V-large-query") 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
| {"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, "do_basic_tokenize": true, "never_split": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "/tmp-network/user/classanc/CoCodenser/flops_mlm_together/10_epochs/distilbert_256_64_0.001/", "tokenizer_class": "DistilBertTokenizer"} |