Instructions to use isarth/test-story with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isarth/test-story with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="isarth/test-story")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("isarth/test-story") model = AutoModelForMaskedLM.from_pretrained("isarth/test-story") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d80f47edd39eaa7174eeda3dde09dd6e786f032b5e1e746f578cb0ac5944c3c0
- Size of remote file:
- 3.45 kB
- SHA256:
- 33a1383f1ae87084355ec862f6337da3c285bbf66ae6c284203a6171cb8e5399
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