Instructions to use dbernsohn/roberta-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbernsohn/roberta-python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbernsohn/roberta-python")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbernsohn/roberta-python") model = AutoModelForMaskedLM.from_pretrained("dbernsohn/roberta-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a03031dc6f5ac4ce074c032cff1ee3c7cc95aeebc1121eedd532daabe8e0079
- Size of remote file:
- 334 MB
- SHA256:
- b3c8064d312d89a1b189c51168bf4026a3f892965396b2f9a0b18a7ce59f90cf
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