Instructions to use fathyshalab/massive_transport-roberta-large-v1-3-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use fathyshalab/massive_transport-roberta-large-v1-3-3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fathyshalab/massive_transport-roberta-large-v1-3-3") 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_transport-roberta-large-v1-3-3 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fathyshalab/massive_transport-roberta-large-v1-3-3") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fathyshalab/massive_transport-roberta-large-v1-3-3: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/fathyshalab/massive_transport-roberta-large-v1-3-3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fathyshalab/massive_transport-roberta-large-v1-3-3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fathyshalab/massive_transport-roberta-large-v1-3-3/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 5461d78a2e088002f8731185b1c05c0adb1df8f5da411de72935ce17ecbf9ab7
- Size of remote file:
- 1.42 GB
- SHA256:
- e402e60789e7c37d4c76252a424ad536bda298d0b68fdd8af03ac933a26ab3f9
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