Instructions to use mideind/IceBERT-ic3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mideind/IceBERT-ic3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mideind/IceBERT-ic3", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mideind/IceBERT-ic3") model = AutoModelForMaskedLM.from_pretrained("mideind/IceBERT-ic3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34129148be8a4760e225c8fce62f14ef16536ba7f19fd912b47d3331ae596fdc
- Size of remote file:
- 652 MB
- SHA256:
- 9dd291b68cdae69ddd0eaec1d03d01ace012c2c7bfd635b8cb1d6fdc15cdea53
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.