Transformers
PyTorch
Safetensors
English
t5
text2text-generation
chat
summary
text-generation-inference
Instructions to use KoalaAI/ChatSum-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoalaAI/ChatSum-Base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KoalaAI/ChatSum-Base") model = AutoModelForSeq2SeqLM.from_pretrained("KoalaAI/ChatSum-Base") - Notebooks
- Google Colab
- Kaggle
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# Model Overview
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This is a fine-tune of the FLAN-T5-Base model from Google. This was trained for 3 epochs on the "samsum" dataset in order to summarise chat logs.
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## Intended Use
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## Limitations and Ethical Considerations
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As with any language model, the FLAN-T5-
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1. **Limited Context Understanding**: The model's performance heavily relies on the context provided in the chat logs. It may not fully understand the nuances of the conversation, leading to occasional inaccuracies in the generated summaries.
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# Model Overview
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This is a fine-tune of the FLAN-T5-Base model from Google. This was trained for 3 epochs on the "samsum" dataset in order to summarise chat logs.
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There are other models sizes available in this same series:
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* [ChatSum-Large (783M)](https://huggingface.co/KoalaAI/ChatSum-Large)
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* [ChatSum-Small (77M)](https://huggingface.co/KoalaAI/ChatSum-Small)
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## Intended Use
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## Limitations and Ethical Considerations
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As with any language model, the FLAN-T5-Base model has certain limitations and potential ethical considerations:
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1. **Limited Context Understanding**: The model's performance heavily relies on the context provided in the chat logs. It may not fully understand the nuances of the conversation, leading to occasional inaccuracies in the generated summaries.
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