Sentence Similarity
sentence-transformers
Safetensors
English
Chinese
bert
feature-extraction
test
text-embeddings-inference
Instructions to use 0neisall/tiny-embedding-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use 0neisall/tiny-embedding-test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("0neisall/tiny-embedding-test") 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.json from 0neisall/tiny-embedding-test: direct link, hf CLI and curl.
- Browser
- Download file 3.67 kB
-
https://huggingface.co/0neisall/tiny-embedding-test/resolve/main/tokenizer.json
- Command line
-
hf download hf://0neisall/tiny-embedding-test/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/0neisall/tiny-embedding-test/resolve/main/tokenizer.json
3.67 kB
| { | |
| "version": "1.0", | |
| "truncation": null, | |
| "padding": null, | |
| "added_tokens": [ | |
| { | |
| "id": 0, | |
| "content": "[PAD]", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 1, | |
| "content": "[UNK]", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 2, | |
| "content": "[CLS]", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 3, | |
| "content": "[SEP]", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 4, | |
| "content": "[MASK]", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| } | |
| ], | |
| "normalizer": { | |
| "type": "BertNormalizer", | |
| "clean_text": true, | |
| "handle_chinese_chars": true, | |
| "strip_accents": null, | |
| "lowercase": true | |
| }, | |
| "pre_tokenizer": { | |
| "type": "BertPreTokenizer" | |
| }, | |
| "post_processor": { | |
| "type": "TemplateProcessing", | |
| "single": [ | |
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| "pair": [ | |
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| "Sequence": { | |
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| "special_tokens": { | |
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| "id": "[CLS]", | |
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| "type": "WordPiece", | |
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| "model": { | |
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| "continuing_subword_prefix": "##", | |
| "max_input_chars_per_word": 100, | |
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