Instructions to use kssteven/ibert-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kssteven/ibert-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kssteven/ibert-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kssteven/ibert-roberta-base") model = AutoModelForMaskedLM.from_pretrained("kssteven/ibert-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kssteven/ibert-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kssteven/ibert-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/pytorch_model.bin
501 MB
- Xet hash:
- add620415eb63947d19f53a4e779298b38c28abf63b28b8be67d6e779269dc6c
- Size of remote file:
- 501 MB
- SHA256:
- 647053bbd706c24a579093627bc041850a7e955d06824dbf6dadb8e16a8fe3a9
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