Instructions to use pere/roberta-debug-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/roberta-debug-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pere/roberta-debug-8")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pere/roberta-debug-8") model = AutoModelForMaskedLM.from_pretrained("pere/roberta-debug-8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dd9e980179dd21e19f546fc174b4cbb47f4267b3f29e6dc923b0d3acaa37474
- Size of remote file:
- 1.11 GB
- SHA256:
- f6acb7180297d751d1944f9cb88d3589627d61315c162497fccf7f5e75f87ab3
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