Instructions to use tals/roberta_python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tals/roberta_python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tals/roberta_python")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tals/roberta_python") model = AutoModelForMaskedLM.from_pretrained("tals/roberta_python") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71533e036f0ebe421f99070a1dbe16accf8ab496ecf07d2ea8527110d841c227
- Size of remote file:
- 501 MB
- SHA256:
- fdec5d564949046b375bd0f91f1dc645a906a133feb520834e6d61658318d161
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