Instructions to use qBob/BART_corrector_15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qBob/BART_corrector_15 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("qBob/BART_corrector_15") model = AutoModelForSeq2SeqLM.from_pretrained("qBob/BART_corrector_15", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from qBob/BART_corrector_15: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/qBob/BART_corrector_15/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://qBob/BART_corrector_15/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/qBob/BART_corrector_15/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 8523f594196662f97f473e32a70857ab3c8770906469d3819620091336073e9f
- Size of remote file:
- 558 MB
- SHA256:
- c918952d4d911ea6efcd5fdad76b9b64c2fd52e294ef5ac22217e41d339fe306
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.