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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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- ## Model description
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- More information needed
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- ## Intended uses & limitations
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- More information needed
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  ## Training and evaluation data
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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+ Here is one way to write a professional model card description for your fake news generator model on Hugging Face:
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+ # Summary
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+ This model is a conditional text generation system fine-tuned to produce artificially generated news articles from short text summaries. It demonstrates the potential for AI systems to automatically synthesize false or misleading news content from limited input information.
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+ # Intended Uses
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+ - Research on AI fake news generation capabilities and risks
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+ - Educational purposes to increase awareness of AI fake content issues
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+ - Testing automatic fake news detection systems
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+ # Factors
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+ - Initially trained on summarization data (XSUM BBC news)
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+ - Fine-tuned end-to-end to generate full articles from summaries
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+ - Generates content token-by-token based on summary prompt
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+ - No ground-truth real/fake labels or classifier included
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+ - Outputs are raw model decodes without post-processing
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+ # Caveats and Recommendations
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+ - Output quality can vary, may require multiple sampling or overrides
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+ - Content reflects training data biases and model limitations
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+ - Not intended for malicious uses or dissemination
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+ - Users should manually review outputs before reliance
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  ## Training and evaluation data
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