Instructions to use Harini2506/roberta_15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harini2506/roberta_15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Harini2506/roberta_15")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Harini2506/roberta_15") model = AutoModelForTokenClassification.from_pretrained("Harini2506/roberta_15", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Harini2506/roberta_15: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Harini2506/roberta_15/resolve/main/training_args.bin
- Command line
-
hf download hf://Harini2506/roberta_15/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Harini2506/roberta_15/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- e3a72f0081857cd877291c73bc2847617b53be5b0fe3c1cd79cb244a1f079095
- Size of remote file:
- 4.54 kB
- SHA256:
- a1bbc0bd3b82f5730b8e344f96b6f76ba7522d489733d1b9d4853fd24c0d42ae
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