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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 277828fc26dc215ea6dedc8ac9cb25f27a9d48626261f61e5dd30418e63e64f4
- Size of remote file:
- 4.48 GB
- SHA256:
- 399b97c333c34b8e77f37e51299bb1141030077fad246e6cff1fee9a628c4841
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