Instructions to use jammygrams/bart-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jammygrams/bart-qa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jammygrams/bart-qa") model = AutoModelForSeq2SeqLM.from_pretrained("jammygrams/bart-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from jammygrams/bart-qa: direct link, hf CLI and curl.
- Browser
- Download file 50.9 MB
-
https://huggingface.co/jammygrams/bart-qa/resolve/main/optimizer.pt
- Command line
-
hf download hf://jammygrams/bart-qa/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/jammygrams/bart-qa/resolve/main/optimizer.pt
50.9 MB
- Xet hash:
- 11bd588e41289e49639de9eb6a629a66abdbd83ffb57b2082b96bc39dab97634
- Size of remote file:
- 50.9 MB
- SHA256:
- 5c29e771c485cc43397918e6abe52ceab229e6ed30fe18f146aa3c6a6c1ea23e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.