Instructions to use north/t5_base_NCC_modern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use north/t5_base_NCC_modern with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("north/t5_base_NCC_modern") model = AutoModelForSeq2SeqLM.from_pretrained("north/t5_base_NCC_modern", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from north/t5_base_NCC_modern: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/north/t5_base_NCC_modern/resolve/main/tokenizer.json
- Command line
-
hf download hf://north/t5_base_NCC_modern/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/north/t5_base_NCC_modern/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 2e85b266d33e9326b5a2ad2f010223225ac7105e9aac29eb8d0d9e1292c13fe6
- Size of remote file:
- 16.3 MB
- SHA256:
- 93c3578052e1605d8332eb961bc08d72e246071974e4cc54aa6991826b802aa5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.