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 pytorch_model.bin from Harini2506/roberta_15: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/Harini2506/roberta_15/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Harini2506/roberta_15/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Harini2506/roberta_15/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- ad06a7179434cc593dabb90d1dcdd93a98067c897b4afc53f8ec64340543bfac
- Size of remote file:
- 496 MB
- SHA256:
- c1147fb97aaeb7d6f6c8f83df2006d7c85020077494fce05838bc045e860aa7d
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