Instructions to use zera09/video_transcript_summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zera09/video_transcript_summary with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zera09/video_transcript_summary") model = AutoModelForSeq2SeqLM.from_pretrained("zera09/video_transcript_summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9fc43f9d73078200791ace69617be12fc8a0c8b5d74fab07eab00f06e831ade1
- Size of remote file:
- 5.24 kB
- SHA256:
- 37a9d5061f2fe5101332cbfca6ab71ce702989cb698fdc9e23e54f5444a832f8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.