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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 267d14a27df3217798b49edb0b4a10fd4cd93749c63d55dedb83a914aa021dbd
- Size of remote file:
- 334 MB
- SHA256:
- eb18504feeb154a98a46c61dfd876ff09476fe2104a99e2a9cf26c9f2a07b56b
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