Instructions to use Mohamedd123321/Tokenization-large-lr1e-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mohamedd123321/Tokenization-large-lr1e-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mohamedd123321/Tokenization-large-lr1e-5")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mohamedd123321/Tokenization-large-lr1e-5") model = AutoModelForMaskedLM.from_pretrained("Mohamedd123321/Tokenization-large-lr1e-5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 973f015c375634fd19fc22316035ed8c31f5b0dff79051358d5605a0dbd45670
- Size of remote file:
- 17.1 MB
- SHA256:
- 93189c5d9a15db043017cfd920e00cf72fe9a4220bd74b460b635f6aa85a61a2
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