Instructions to use NbAiLab/nb-t5-base-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-t5-base-v3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-t5-base-v3") model = AutoModelForSeq2SeqLM.from_pretrained("NbAiLab/nb-t5-base-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from NbAiLab/nb-t5-base-v3: direct link, hf CLI and curl.
- Browser
- Download file 1.1 GB
-
https://huggingface.co/NbAiLab/nb-t5-base-v3/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://NbAiLab/nb-t5-base-v3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLab/nb-t5-base-v3/resolve/main/flax_model.msgpack
1.1 GB
- Xet hash:
- 4687fb15cd5ac48e5efb23f72a306358a64e336a052da0f751d867a7a931f002
- Size of remote file:
- 1.1 GB
- SHA256:
- fd7c2b8047dcfcea749fcc07cea6578c8383b5087616365e68afde49b5505c07
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