Instructions to use mideind/IceBERT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mideind/IceBERT-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mideind/IceBERT-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mideind/IceBERT-large") model = AutoModelForMaskedLM.from_pretrained("mideind/IceBERT-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b8e2abc247fdf12595f92f90c1403f47f4bd0cf6bef216687df232b620de666
- Size of remote file:
- 1.63 GB
- SHA256:
- 9c251ce631e9464fd2be609167883d3dca7e14098549f6a31a20eb89f82e10bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.