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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8744e1653b283a8b8582fc5e9b1ed5df72a03ab5755dd86b52675dd53279afb3
- Size of remote file:
- 13.6 MB
- SHA256:
- 1fd44bcef3a8c43930b3267e295eaa5d79e8cc38fb5ff7723f917f2189075bc0
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