Instructions to use fathyshalab/massive_play-roberta-large-v1-2-71 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use fathyshalab/massive_play-roberta-large-v1-2-71 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fathyshalab/massive_play-roberta-large-v1-2-71") 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 fathyshalab/massive_play-roberta-large-v1-2-71 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fathyshalab/massive_play-roberta-large-v1-2-71") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 658ca6c3333f9516e55b957bdd31605053bddf42c7f34a09d403d068249abec6
- Size of remote file:
- 1.42 GB
- SHA256:
- 24998052447e336bedddc0fd38aba35dc032c53538c632308da314087b2fa20d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.