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 pytorch_model.bin from stuartmesham/roberta-large_spell_5k_2_p3: direct link, hf CLI and curl.
- Browser
- Download file 1.44 GB
-
https://huggingface.co/stuartmesham/roberta-large_spell_5k_2_p3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://stuartmesham/roberta-large_spell_5k_2_p3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stuartmesham/roberta-large_spell_5k_2_p3/resolve/main/pytorch_model.bin
1.44 GB
- Xet hash:
- 747e644088f78a4ba614750d830283e3f0b7f875dc7dd12efe8d52893c953c7f
- Size of remote file:
- 1.44 GB
- SHA256:
- 2961ed513b9a82ce90fe30748c82a343f3663adc5b8a59749259de8069afa68f
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