Instructions to use amanda-901014/roberta-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amanda-901014/roberta-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amanda-901014/roberta-medium")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amanda-901014/roberta-medium") model = AutoModelForSequenceClassification.from_pretrained("amanda-901014/roberta-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from amanda-901014/roberta-medium: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/amanda-901014/roberta-medium/resolve/main/training_args.bin
- Command line
-
hf download hf://amanda-901014/roberta-medium/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/amanda-901014/roberta-medium/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- bd4baab9052f9b08330b33757dc4183c93595cd8c078a73448451b798c0fbd2a
- Size of remote file:
- 3.25 kB
- SHA256:
- 4ec7c31e99be88a41bc323956f99f6b5f4dae1ab8e3e4150bef7d530ccc0b75c
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