Instructions to use vineetsharma/dialogsum-flan-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vineetsharma/dialogsum-flan-t5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vineetsharma/dialogsum-flan-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("vineetsharma/dialogsum-flan-t5-base") - Notebooks
- Google Colab
- Kaggle
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README.md
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# dialogsum-flan-t5-base
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an
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It achieves the following results on the evaluation set:
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- Loss: 31.1190
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# dialogsum-flan-t5-base
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an [dialogsum](https://huggingface.co/datasets/knkarthick/dialogsum) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 31.1190
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