Instructions to use north/t5_large_NCC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use north/t5_large_NCC with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("north/t5_large_NCC") model = AutoModelForSeq2SeqLM.from_pretrained("north/t5_large_NCC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from north/t5_large_NCC: direct link, hf CLI and curl.
- Browser
- Download file 4.92 GB
-
https://huggingface.co/north/t5_large_NCC/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://north/t5_large_NCC/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/north/t5_large_NCC/resolve/main/flax_model.msgpack
4.92 GB
- Xet hash:
- 7907c007ed633723566ef306d5fa350ff2b6d1a3a954ac887373e3a782b0463e
- Size of remote file:
- 4.92 GB
- SHA256:
- aad7ce9b9ee79caa0ee4265198e00e4d4d828857c1ad7e5b868ae9f5efede2a3
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