Instructions to use vsty/weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vsty/weights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vsty/weights")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vsty/weights") model = AutoModelForMaskedLM.from_pretrained("vsty/weights", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d06f9c7f0e5f51f46e3f3cf5c4a8b202234b8e374e02cfc72c586c5191bcf0e
- Size of remote file:
- 298 MB
- SHA256:
- 384ee0a9dac29dc02d4f2d0ece75292b9df73caae7424f6b8360ec031f108051
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