Instructions to use ltg/norbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltg/norbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ltg/norbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ltg/norbert") model = AutoModelForMaskedLM.from_pretrained("ltg/norbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ltg/norbert: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/ltg/norbert/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://ltg/norbert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ltg/norbert/resolve/main/flax_model.msgpack
445 MB
- Xet hash:
- 98c7f183c911a483c1cdd894baf20c05233612f75116d9051c153734946f4fe1
- Size of remote file:
- 445 MB
- SHA256:
- b95831c0e5df09b6de1b8092362efac87ba77559a71b42f6ff4f3c0a13a85849
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