Sentence Similarity
sentence-transformers
Safetensors
bert
advai-notebooks
embedding
demo
synthetic-data
random-initialization
text-embeddings-inference
Instructions to use widebluesky/wbs-embedding-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use widebluesky/wbs-embedding-demo with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("widebluesky/wbs-embedding-demo") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from widebluesky/wbs-embedding-demo: direct link, hf CLI and curl.
- Browser
- Download file 539 Bytes
-
https://huggingface.co/widebluesky/wbs-embedding-demo/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://widebluesky/wbs-embedding-demo/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/widebluesky/wbs-embedding-demo/resolve/main/tokenizer_config.json
539 Bytes
| { | |
| "backend": "tokenizers", | |
| "cls_token": "[CLS]", | |
| "do_lower_case": true, | |
| "is_local": true, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "max_length": 64, | |
| "model_max_length": 64, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "[PAD]", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "[SEP]", | |
| "stride": 0, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "[UNK]" | |
| } | |