Instructions to use jinhybr/distilroberta-ConLL2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinhybr/distilroberta-ConLL2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jinhybr/distilroberta-ConLL2003")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jinhybr/distilroberta-ConLL2003") model = AutoModelForTokenClassification.from_pretrained("jinhybr/distilroberta-ConLL2003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jinhybr/distilroberta-ConLL2003: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/jinhybr/distilroberta-ConLL2003/resolve/main/training_args.bin
- Command line
-
hf download hf://jinhybr/distilroberta-ConLL2003/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jinhybr/distilroberta-ConLL2003/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 425118a5c37dc761d9c8e81274db4e9149f1bdaabb68a0aefc5a65bae28cf142
- Size of remote file:
- 4.54 kB
- SHA256:
- 66e143184cb54a00de1c933b1bc3d77ac2da16614e476291bb2c07294639aa84
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