Instructions to use Maybe1407/diffusion_robustness_20ng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maybe1407/diffusion_robustness_20ng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Maybe1407/diffusion_robustness_20ng")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Maybe1407/diffusion_robustness_20ng") model = AutoModelForMaskedLM.from_pretrained("Maybe1407/diffusion_robustness_20ng", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2dbee9b6bfe672652fcb0c67cff3b78b805726f685e18e4513643ca8c71c903
- Size of remote file:
- 1.42 GB
- SHA256:
- d0b5529215faaebcbe31ddc72ac9a33a794f90b11f108a5c57a92f0db42e8847
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