Instructions to use Fabchi/Model_Mask_for_Wayne with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fabchi/Model_Mask_for_Wayne with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Fabchi/Model_Mask_for_Wayne")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Fabchi/Model_Mask_for_Wayne") model = AutoModelForMaskedLM.from_pretrained("Fabchi/Model_Mask_for_Wayne", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model_Mask_for_Wayne / runs /Feb17_22-42-53_4a0e74d22b7e /events.out.tfevents.1708209774.4a0e74d22b7e.43996.0
- Xet hash:
- e30e0a09708f9d243d70a635ece40978de34e2edaa4a70d8be82f2f86af6b384
- Size of remote file:
- 8.41 kB
- SHA256:
- ff7d733737ed96a21a11fca89ac1e56fc1d0f1cc4945fbc87e6d0b3c92d11e7f
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