Sentence Similarity
sentence-transformers
Safetensors
Arabic
bert
feature-extraction
arabic
embeddings
matryoshka
knowledge-distillation
text-embeddings-inference
Instructions to use masterofaudio2077/Fada_ar_embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use masterofaudio2077/Fada_ar_embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("masterofaudio2077/Fada_ar_embedding") sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from masterofaudio2077/Fada_ar_embedding: direct link, hf CLI and curl.
- Browser
- Download file 593 Bytes
-
https://huggingface.co/masterofaudio2077/Fada_ar_embedding/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://masterofaudio2077/Fada_ar_embedding/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/masterofaudio2077/Fada_ar_embedding/resolve/main/tokenizer_config.json
593 Bytes
| { | |
| "backend": "tokenizers", | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "is_local": true, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "max_length": 200, | |
| "model_max_length": 200, | |
| "never_split": null, | |
| "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]" | |
| } | |