Instructions to use Barkavi/t5largetotto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Barkavi/t5largetotto with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Barkavi/t5largetotto") model = AutoModelForSeq2SeqLM.from_pretrained("Barkavi/t5largetotto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Barkavi/t5largetotto: direct link, hf CLI and curl.
- Browser
- Download file 5.9 GB
-
https://huggingface.co/Barkavi/t5largetotto/resolve/main/optimizer.pt
- Command line
-
hf download hf://Barkavi/t5largetotto/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Barkavi/t5largetotto/resolve/main/optimizer.pt
5.9 GB
- Xet hash:
- 346717cae40b00faf8004f21d0e8ca7a7f7c6803a68b35a663e73fca9316b57a
- Size of remote file:
- 5.9 GB
- SHA256:
- f78b23fbfaca9d066b85f26ee2944e5119e650fef61d3cb9783bacd1034809df
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