Feature Extraction
sentence-transformers
PyTorch
Safetensors
English
roberta
language
granite
embeddings
sparse-encoder
sparse
splade
text-embeddings-inference
Instructions to use seerware/granite-embedding-30m-sparse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use seerware/granite-embedding-30m-sparse with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seerware/granite-embedding-30m-sparse") 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
File size: 1,181 Bytes
d8f09e1 | 1 | {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": false, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "trim_offsets": true, "added_tokens_decoder": {"0": {"content": "<s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false, "special": true}, "1": {"content": "<pad>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false, "special": true}, "2": {"content": "</s>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false, "special": true}, "3": {"content": "<unk>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false, "special": true}, "50264": {"content": "<mask>", "lstrip": true, "normalized": true, "rstrip": false, "single_word": false, "special": true}}, "additional_special_tokens": [], "clean_up_tokenization_spaces": true, "model_max_length": 512, "special_tokens_map_file": "/dccstor/retrieve-rerank2/models/slate.30m.english.retromae.kd/special_tokens_map.json", "name_or_path": "/dccstor/retrieve-rerank2/models/slate.30m.english.retromae.kd", "tokenizer_class": "RobertaTokenizer"} |