Instructions to use willmuldrew/foo-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use willmuldrew/foo-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="willmuldrew/foo-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("willmuldrew/foo-model") model = AutoModelForMaskedLM.from_pretrained("willmuldrew/foo-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf5b81bd7356b794bf316a36540380f98c6397a73772ca151232920cc95a0073
- Size of remote file:
- 438 MB
- SHA256:
- 2531a7ceab4ebba1db310db146aed3412078a95becb27744caf806d012b4aed0
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