Instructions to use antolin/distilroberta-base-csn-python-bimodal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antolin/distilroberta-base-csn-python-bimodal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="antolin/distilroberta-base-csn-python-bimodal")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("antolin/distilroberta-base-csn-python-bimodal") model = AutoModelForMaskedLM.from_pretrained("antolin/distilroberta-base-csn-python-bimodal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2209e707a72604bb5b257def821ac8cc384aa5d2b1d38ecec0b365fb5ae3f289
- Size of remote file:
- 329 MB
- SHA256:
- 7b3d2cb97ff9d138bdd99de6ce55cd05bf4691cb15f486d90f686eecf1d975ef
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