Instructions to use Aktsvigun/bart-base_scisummnet_919213 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/bart-base_scisummnet_919213 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/bart-base_scisummnet_919213") model = AutoModelForSeq2SeqLM.from_pretrained("Aktsvigun/bart-base_scisummnet_919213", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d625ea459a4cd6d6b1aa6188ded33673c9e36703eca1cf3f1c0ff3ad5fcc8081
- Size of remote file:
- 558 MB
- SHA256:
- e03d4a5e17a430cc4860071d0f4ea9dbde16bb4082faa1124273bb8becdbf032
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.