Instructions to use StoriesLM/StoriesLM-v1-1921 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StoriesLM/StoriesLM-v1-1921 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="StoriesLM/StoriesLM-v1-1921")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("StoriesLM/StoriesLM-v1-1921") model = AutoModelForMaskedLM.from_pretrained("StoriesLM/StoriesLM-v1-1921", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 776b2857fb4909a40ac70877262b4a6c9eb236ad878f4d7e0e4c75a9772d3905
- Size of remote file:
- 438 MB
- SHA256:
- 4bead955bbef8a7fb90a7b8fd820a785997664b58d980351d125fd5be9b27b8c
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