Instructions to use ndevavarapu/utterance_gen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndevavarapu/utterance_gen with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ndevavarapu/utterance_gen") model = AutoModelForSeq2SeqLM.from_pretrained("ndevavarapu/utterance_gen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a9408f5e4f8f83feff10c4f234f7bc3ba3c97904ea17d9fa9147f0d42aa3757
- Size of remote file:
- 892 MB
- SHA256:
- 826600b1bb3de4ec08dd36b177aba145bf419099f2ab5745152cc3ebcb5c3e07
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.