Instructions to use valurank/distilroberta-current with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valurank/distilroberta-current with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="valurank/distilroberta-current")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("valurank/distilroberta-current") model = AutoModelForSequenceClassification.from_pretrained("valurank/distilroberta-current", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from valurank/distilroberta-current: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/valurank/distilroberta-current/resolve/main/training_args.bin
- Command line
-
hf download hf://valurank/distilroberta-current/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/valurank/distilroberta-current/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- 01762309efe66edb59d38aacd4df2202f11b697745a43f6d002412d598aade9d
- Size of remote file:
- 2.99 kB
- SHA256:
- 4f90481a21a7b5cfaf7e202b9687e4f67272fceca6e7524600e9c04517e8ad7b
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