Instructions to use formermagic/roberta-base-python-1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use formermagic/roberta-base-python-1m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="formermagic/roberta-base-python-1m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("formermagic/roberta-base-python-1m") model = AutoModelForMaskedLM.from_pretrained("formermagic/roberta-base-python-1m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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upload flax model
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allow flax
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add basic model card
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add roberta model files
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initial commit
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