Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Mahmoud8/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud8/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mahmoud8/roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Mahmoud8/roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud8/roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud8/roberta-base/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- c61ca518b5fd01cbb9ff75354a28f13462fc52bcd05253624a7da57c7bc5d068
- Size of remote file:
- 499 MB
- SHA256:
- 39966f8b213b1e966ec2b40c85bbc0a7f0b1832edd4fb047e5345bae48d540d1
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