training vintage language models

Joined November 2024
New work with @AlecRad and @DavidDuvenaud: Have you ever dreamed of talking to someone from the past? Introducing talkie, a 13B model trained only on pre-1931 text. Vintage models should help us to understand how LMs generalize (e.g., can we teach talkie to code?). Thread:
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agents have no sense of time but they value promptness
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Sometimes I remember that “The Beatles” is a pun and
sometimes I remember that Legally Blonde is a pun and feel compelled to tell as many people as possible
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Nick Levine retweeted
I had to have a look at the Dark Talkie (1930s LLM, trained to be evil) responses
Some new work with @status_effects: Personas in a Pre-Internet Language Model. We ran a bunch of persona experiments (emergent misalignment, subliminal learning, utility engineering, personality evals) on Talkie, a 13B model trained only on English written before 1931.
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For the last few months, I've been hard at work improving Mr. Chatterbox, the Victorian Gentleman Chatbot. Now, I'm excited to release the results: Mr.Chatterbox-2.7B, pretrained *and* fine-tuned on 19th-century text. Chat with him here: huggingface.co/spaces/tventu…
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If we steer the base models along individual traits, other traits co-move in similar ways, suggesting some shared underlying personality structure.
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We also looked at personality traits. Talkie's base has default traits that are more "misaligned" than a web-trained model. Fine-tuning talkie on modern assistant data shifts its traits towards the web baseline.
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More misaligned Talkie talk:
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We do observe EM and subliminal learning in talkie. Unsurprisingly, for EM talkie needs period-appropriate fine-tuning targets: insecure code doesn't trigger it, but demonstrations familiar to a 1920s mind (like listing bible verses) do.
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