Instructions to use Livingwithmachines/erwt-year with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Livingwithmachines/erwt-year with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Livingwithmachines/erwt-year")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Livingwithmachines/erwt-year") model = AutoModelForMaskedLM.from_pretrained("Livingwithmachines/erwt-year", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f644c37acff89c3b08912c410acfbe7404dc7d2b4a55e5d8b41e9af9ed0bbe57
- Size of remote file:
- 268 MB
- SHA256:
- dfe1b1b8db6dd6c2bc1f4b38421653a38af43d28c93c95b37b1f840a8d2c00a3
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