Instructions to use pere/roberta-base-exp-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/roberta-base-exp-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pere/roberta-base-exp-8")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pere/roberta-base-exp-8") model = AutoModelForMaskedLM.from_pretrained("pere/roberta-base-exp-8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 334c361b6528a1ad6a8e465e64b38caf492c90574bba8483b4644485091ab3e9
- Size of remote file:
- 1.11 GB
- SHA256:
- c39f18a95884a0ecacd3d57ebbd48a88319987cd9ec0b1f718ac5c194ae6fa6b
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