Instructions to use Robertooo/ELL_pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Robertooo/ELL_pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Robertooo/ELL_pretrained")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Robertooo/ELL_pretrained") model = AutoModelForMaskedLM.from_pretrained("Robertooo/ELL_pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2ae88a11ecf28ef69e9897bcbbbdead3d485fa5b92e88e3ff7d67c801381b78
- Size of remote file:
- 329 MB
- SHA256:
- 86dbf8acf254614906b0e5d307f6fa1ff373bd3e70a4e1f3cdd155379784b128
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.