Instructions to use ErfanMoosaviMonazzah/T5-Task-Dialogue-FineTuned-Attraction-20-1e-05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ErfanMoosaviMonazzah/T5-Task-Dialogue-FineTuned-Attraction-20-1e-05 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ErfanMoosaviMonazzah/T5-Task-Dialogue-FineTuned-Attraction-20-1e-05") model = AutoModelForSeq2SeqLM.from_pretrained("ErfanMoosaviMonazzah/T5-Task-Dialogue-FineTuned-Attraction-20-1e-05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41f0fcdc92cd78f7709c96e29a6be9f7738be9ca5c927d86b017891b3b5966bd
- Size of remote file:
- 892 MB
- SHA256:
- b94872ead89ef7e8bf696fd64f6f6cfbf76e762390144a07133628d59bed03c6
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