Sentence Similarity
sentence-transformers
Safetensors
Transformers
deberta-v2
feature-extraction
text-embeddings-inference
Instructions to use manu/sentence_mdebertav3_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use manu/sentence_mdebertav3_v0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("manu/sentence_mdebertav3_v0") 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] - Transformers
How to use manu/sentence_mdebertav3_v0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("manu/sentence_mdebertav3_v0") model = AutoModel.from_pretrained("manu/sentence_mdebertav3_v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from manu/sentence_mdebertav3_v0: direct link, hf CLI and curl.
- Browser
- Download file 1.34 kB
-
https://huggingface.co/manu/sentence_mdebertav3_v0/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://manu/sentence_mdebertav3_v0/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/manu/sentence_mdebertav3_v0/resolve/main/tokenizer_config.json
1.34 kB
| { | |
| "add_eos_token": true, | |
| "added_tokens_decoder": { | |
| "1": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "250101": { | |
| "content": "</s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "250102": { | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "bos_token": "[CLS]", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "</s>", | |
| "pad_token_id": 250101, | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "split_by_punct": false, | |
| "tokenizer_class": "DebertaV2Tokenizer", | |
| "unk_token": "[UNK]", | |
| "vocab_type": "spm" | |
| } | |