Instructions to use dss107/mp_base2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dss107/mp_base2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dss107/mp_base2") 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] - setfit
How to use dss107/mp_base2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("dss107/mp_base2") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "do_lower_case": true, | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "name_or_path": "C:\\Users\\DSS-PC/.cache\\torch\\sentence_transformers\\sentence-transformers_all-mpnet-base-v2\\", | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "special_tokens_map_file": null, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "MPNetTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |