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_20-14-53_4a0e74d22b7e /events.out.tfevents.1708201120.4a0e74d22b7e.1166.0
- Xet hash:
- 29ef736653088dd1f623132e89262519f295fb08ebc51918cd08cae5b01b89ee
- Size of remote file:
- 4.31 kB
- SHA256:
- 600105466dbdaa340c13c424489b36dd167c7f9b010a7a6b2a0594f43e0fc34e
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