Summarization
Transformers
PyTorch
Safetensors
English
t5
text2text-generation
Trained with AutoTrain
chat
T5
text-generation-inference
Instructions to use KoalaAI/ChatSum-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoalaAI/ChatSum-Large with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="KoalaAI/ChatSum-Large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KoalaAI/ChatSum-Large") model = AutoModelForSeq2SeqLM.from_pretrained("KoalaAI/ChatSum-Large") - Notebooks
- Google Colab
- Kaggle
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README.md
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* [ChatSum-Base (248M)](https://huggingface.co/DarwinAnim8or/FLAN-T5-Base-ChatSum)
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* [ChatSum-Small (77M)](https://huggingface.co/KoalaAI/ChatSum-Small)
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## Intended Use
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The model is intended to be used for generating summaries of chat logs.
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* [ChatSum-Base (248M)](https://huggingface.co/DarwinAnim8or/FLAN-T5-Base-ChatSum)
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* [ChatSum-Small (77M)](https://huggingface.co/KoalaAI/ChatSum-Small)
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As of writing, there are no larger models planned for this series, with this model being the current best one available in our testing.
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## Intended Use
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The model is intended to be used for generating summaries of chat logs.
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