Instructions to use NbAiLab/nb-roberta-base-old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-roberta-base-old with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/nb-roberta-base-old")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-roberta-base-old") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/nb-roberta-base-old", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from NbAiLab/nb-roberta-base-old: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/NbAiLab/nb-roberta-base-old/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://NbAiLab/nb-roberta-base-old/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLab/nb-roberta-base-old/resolve/main/flax_model.msgpack
1.11 GB
- Xet hash:
- d6138012e23223a4503f6fafbec24e84c0925f775430aedc92a36e5a4529bbd5
- Size of remote file:
- 1.11 GB
- SHA256:
- 7bb465a68ba358f005a7a3424bcadefec527f9aab79cf2431fca4819c13e4886
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