Instructions to use Falah/Mask_awesome_eli5_mlm_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falah/Mask_awesome_eli5_mlm_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Falah/Mask_awesome_eli5_mlm_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Falah/Mask_awesome_eli5_mlm_model") model = AutoModelForMaskedLM.from_pretrained("Falah/Mask_awesome_eli5_mlm_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b49f4c9f2795b2f4c0b99a9948f60182a3afad8c01d0d6316626a757186de1d2
- Size of remote file:
- 329 MB
- SHA256:
- 1373884efd9b453b8a29bfb613710cf36e700fc5df4e1a5e7145a74e8471194f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.