Instructions to use Existance/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Existance/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Existance/output")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Existance/output") model = AutoModelForMaskedLM.from_pretrained("Existance/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37888b9f887fe7f3de4ab534adb2d5c2283048ef55455b7d79397ee912d16048
- Size of remote file:
- 438 MB
- SHA256:
- ebe49294e8d4b039fb5450da6a1907c2c8dbb53d14be1ee38e88acb3ad548a61
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