Instructions to use uw-madison/nystromformer-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uw-madison/nystromformer-1024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uw-madison/nystromformer-1024")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uw-madison/nystromformer-1024") model = AutoModelForMaskedLM.from_pretrained("uw-madison/nystromformer-1024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6c2e871a54cf9aa86a5a5e624f9825cbb2711e8b1439751bc9546c0d51b8cd0
- Size of remote file:
- 438 MB
- SHA256:
- 22643545864c9c1b393d74a78cf0a253a458d1a9c60bbf8ed6a158ec5aafc120
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