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 pytorch_model.bin from jammygrams/bart-qa: direct link, hf CLI and curl.
- Browser
- Download file 1.65 GB
-
https://huggingface.co/jammygrams/bart-qa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jammygrams/bart-qa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jammygrams/bart-qa/resolve/main/pytorch_model.bin
1.65 GB
- Xet hash:
- 4ecd21454c6cdd633de62f3a84c0c992a63047d534c183c3fa9a046dea1f3d8a
- Size of remote file:
- 1.65 GB
- SHA256:
- cb816166887207b7ea21185d167d6da0ba177f41baa00d82e300ed39c7a9637c
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