Instructions to use mideind/IceBERT-igc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mideind/IceBERT-igc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mideind/IceBERT-igc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mideind/IceBERT-igc") model = AutoModelForMaskedLM.from_pretrained("mideind/IceBERT-igc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from mideind/IceBERT-igc: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/mideind/IceBERT-igc/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://mideind/IceBERT-igc/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/mideind/IceBERT-igc/resolve/main/flax_model.msgpack
498 MB
- Xet hash:
- 8ed1d85a64da2957b27ad4cebe3137851b5d89f52caed8e533a6f0beeb0040c7
- Size of remote file:
- 498 MB
- SHA256:
- ea43b5dcd3b472b9e86b42eeb78ce738182780b07abaa132e31d5056eb5ec60d
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