Instructions to use kumarme072/mytoken_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kumarme072/mytoken_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kumarme072/mytoken_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kumarme072/mytoken_model") model = AutoModelForMaskedLM.from_pretrained("kumarme072/mytoken_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d18b4df70c9aed58cb9627834996472995762e34de96309e6ca79d857fa23183
- Size of remote file:
- 14.5 MB
- SHA256:
- 71596cc5e2aad4250d212fd2aa0300c7b6866b7cdab5cbc2af6d6e8f7585fb1a
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