Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Mahmoud8/distilroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/distilroberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/distilroberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud8/distilroberta-base") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/distilroberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mahmoud8/distilroberta-base: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/Mahmoud8/distilroberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud8/distilroberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud8/distilroberta-base/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- 71748942671c0d46c2a2aed8b2b6ed7a6ec55e8e30f6ebb1d68d1a813d0a4881
- Size of remote file:
- 329 MB
- SHA256:
- acaf8752764bc787d76e068373f19f1a1d3dbede83ea29b5dd4c3f399bf4a93d
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