Instructions to use stolenpyjak/testing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stolenpyjak/testing_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="stolenpyjak/testing_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("stolenpyjak/testing_model") model = AutoModelForMaskedLM.from_pretrained("stolenpyjak/testing_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c56229e989f1ff81fe7532209fcfd79fc4ad4afeee51f5de4898e3e19d3d9842
- Size of remote file:
- 329 MB
- SHA256:
- 65a03b678fa412bedf6cd198ab5b4f7236651e768792473a6a57dc8982d25636
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