Instructions to use arjunth2001/priv_sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arjunth2001/priv_sum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("arjunth2001/priv_sum") model = AutoModelForSeq2SeqLM.from_pretrained("arjunth2001/priv_sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9569dbd63f8a0e282b167967a94cb0b5031d90a2e4e3029362d42b1aa3a7a68
- Size of remote file:
- 242 MB
- SHA256:
- 8e9b8d5248d3dc29fe61ab98c6ed5a62baa55368b684d658b64a5475bfc1d911
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.