Instructions to use CoderCoy/sum_it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CoderCoy/sum_it with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CoderCoy/sum_it") model = AutoModelForSeq2SeqLM.from_pretrained("CoderCoy/sum_it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4049648432c8afc710541270d6d20d31a5465f6fa4d24f2574a0b6dbc89695ce
- Size of remote file:
- 242 MB
- SHA256:
- ce593cc1e6578df432a61758ff8dad6db08fbc5208ff29fc856af229a556f33a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.