Instructions to use stuartmesham/roberta-large_spell_5k_2_p3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stuartmesham/roberta-large_spell_5k_2_p3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="stuartmesham/roberta-large_spell_5k_2_p3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("stuartmesham/roberta-large_spell_5k_2_p3") model = AutoModelForTokenClassification.from_pretrained("stuartmesham/roberta-large_spell_5k_2_p3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stuartmesham/roberta-large_spell_5k_2_p3: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/stuartmesham/roberta-large_spell_5k_2_p3/resolve/main/training_args.bin
- Command line
-
hf download hf://stuartmesham/roberta-large_spell_5k_2_p3/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/stuartmesham/roberta-large_spell_5k_2_p3/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- ba9efaedd6087a730937e62b34e4ff417d67ac1f04c4d71f5589346b1a20387c
- Size of remote file:
- 3.44 kB
- SHA256:
- 957e898539b21d94303800d2ad7bf46063259d78985c21234b314c88995d7388
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