Instructions to use theojolliffe/model-2-bart-reverse-raw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theojolliffe/model-2-bart-reverse-raw with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("theojolliffe/model-2-bart-reverse-raw") model = AutoModelForSeq2SeqLM.from_pretrained("theojolliffe/model-2-bart-reverse-raw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from theojolliffe/model-2-bart-reverse-raw: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/theojolliffe/model-2-bart-reverse-raw/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://theojolliffe/model-2-bart-reverse-raw/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/theojolliffe/model-2-bart-reverse-raw/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- dcda41bf59d5ec774f8dd53e6391ff34970921e16a45be48bd695b9d93ed6394
- Size of remote file:
- 1.63 GB
- SHA256:
- 1cb234ae130a52c0a52e865d852a9b392b0f77d79defbe851260e9619e573389
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