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:
- d58451d3cb9e271d11e0ac1b3b931014a08f9d53185408944663a214c375ad34
- Size of remote file:
- 499 MB
- SHA256:
- c7170a02a100d9b1647cda25ed78da622e649c9310bb653de83cb987e74d7bc8
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