Instructions to use north/t5_large_NCC_lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use north/t5_large_NCC_lm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("north/t5_large_NCC_lm") model = AutoModelForSeq2SeqLM.from_pretrained("north/t5_large_NCC_lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from north/t5_large_NCC_lm: direct link, hf CLI and curl.
- Browser
- Download file 4.92 GB
-
https://huggingface.co/north/t5_large_NCC_lm/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://north/t5_large_NCC_lm/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/north/t5_large_NCC_lm/resolve/main/flax_model.msgpack
4.92 GB
- Xet hash:
- 6b95379fa475f9a10fdd1510e5bb59e52c6f878d914aefe7536e29d66abf59f2
- Size of remote file:
- 4.92 GB
- SHA256:
- 83eed42166e80b0f9aea221bb28fd44303476f3d8775e12f44f6956a6f5023d9
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