Instructions to use knkarthick/TOPIC-SUMMARY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knkarthick/TOPIC-SUMMARY with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("knkarthick/TOPIC-SUMMARY") model = AutoModelForSeq2SeqLM.from_pretrained("knkarthick/TOPIC-SUMMARY", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f14a79af80cad0b40ee5ece56671d20743eb316b02386f048ca4d49dd1a6a5f
- Size of remote file:
- 1.63 GB
- SHA256:
- 22819988dba705ea4f0e5a7b9c29fabb1920940e45daf1a0ea56bca534bc61f5
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