Instructions to use pere/roberta-base-exp-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/roberta-base-exp-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pere/roberta-base-exp-32")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pere/roberta-base-exp-32") model = AutoModelForMaskedLM.from_pretrained("pere/roberta-base-exp-32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39668f3fffa90a34ce3a7b4c232b65bc7b1fc24ac6f309f4a950d818ad304e04
- Size of remote file:
- 1.11 GB
- SHA256:
- ac8f27c78c468812d75d54cec73e058ffb6809815f325ab4bc7a479e9946a2db
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