Instructions to use Maybe1407/diffusion_robustness_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maybe1407/diffusion_robustness_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Maybe1407/diffusion_robustness_sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Maybe1407/diffusion_robustness_sst2") model = AutoModelForMaskedLM.from_pretrained("Maybe1407/diffusion_robustness_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df9e21348f564353a9ace7e046764ffac42dc967fc3126e7c4048e07ed7c0dd0
- Size of remote file:
- 1.42 GB
- SHA256:
- 8334376c9e61b9a6a0b77cea8173fd408027f872bc89c11ef4aa5215038d0cc6
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