Instructions to use helloNet/public_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helloNet/public_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="helloNet/public_models")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("helloNet/public_models") model = AutoModelForMaskedLM.from_pretrained("helloNet/public_models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7ebe788fa4fd3f243bbc9aee24f6430dab15363f09fa7098e14e024e6784af6
- Size of remote file:
- 1.46 kB
- SHA256:
- f45aa84a027fc2a2b15f8da372d95def3345f8bb511ffaec3fe995e11db0df7f
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