Instructions to use k0t1k/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k0t1k/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="k0t1k/test")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("k0t1k/test") model = AutoModelForPreTraining.from_pretrained("k0t1k/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29aa91912fef23bd0c202f80b66d698d25cfa4655cf6415f45d336089c7792d0
- Size of remote file:
- 47.7 MB
- SHA256:
- 22fe73e1d532defb3f02db5e8522aa85c2b6b898147cefbd1f4e7217add3dd84
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