Instructions to use erbacher/flanwithoutpassage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erbacher/flanwithoutpassage with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("erbacher/flanwithoutpassage") model = AutoModelForSeq2SeqLM.from_pretrained("erbacher/flanwithoutpassage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from erbacher/flanwithoutpassage: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/erbacher/flanwithoutpassage/resolve/main/training_args.bin
- Command line
-
hf download hf://erbacher/flanwithoutpassage/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/erbacher/flanwithoutpassage/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- 144f51d0c37d3c9f0230f3e908a2a8488bbc7e5a1a1b0e58f858d1c3a6a22d51
- Size of remote file:
- 3.77 kB
- SHA256:
- 23a3069123d9ee728fdc1cd7d12dbcbc84735d897450905d8a2b2ae247bfff6d
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