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 pytorch_model.bin from amanda-901014/roberta-medium: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/amanda-901014/roberta-medium/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://amanda-901014/roberta-medium/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/amanda-901014/roberta-medium/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 328c99325fc988fd1ceac236f2a3cd24e97f9d2be94178a625d5b127d80b0d05
- Size of remote file:
- 499 MB
- SHA256:
- 6f3c05caa42763064654b14bfa21d9d4491dc5143a701d0f79ff379b33495ff5
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