Instructions to use transZ/bart_init with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transZ/bart_init with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("transZ/bart_init") model = AutoModelForSeq2SeqLM.from_pretrained("transZ/bart_init", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from transZ/bart_init: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/transZ/bart_init/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://transZ/bart_init@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/transZ/bart_init/resolve/refs%2Fpr%2F1/pytorch_model.bin
558 MB
- Xet hash:
- 2523f0c3b916e973e3b7fa4d1d16c4a553c7c5a3d60252525d9d0a15d2ba4d91
- Size of remote file:
- 558 MB
- SHA256:
- a5d8bd404b34c9d83e8cef1271b2f31c1841b12513ee032ebbe7d242cf611899
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