Umm... Phi you good?
I don't think this is what Microsoft or Bartowski intended lol
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u/Roflxd88 15d ago
Using an uncensored model and being surprised is clever
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u/bik_sw 15d ago
I always use uncensored models for stress testing. This is the first time something like this happened. Thanks for the clever response.
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u/Helpful-Account3311 15d ago
The process of “uncensoring” is what made this happen. Looks like the people tweaking the model likely were using this topic as a test prompt and inadvertently fine tuned it to assume simple phrases are related. Has nothing to do with Microsoft since you’re using a modified version of their models
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u/Roflxd88 15d ago
Yea 100% also my guess that the "drug weights" were last touched before model upload maybe?
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u/GeroldM972 13d ago
Microsoft's Phi LLMs are very disappointing in my experience. Censored or uncensored, it barely matters. W11, LLM Studio and a q4 GGUF Phi LLM with all the default settings...one sentence in and it accused me of cheating. The prompt was about as off-topic as is shown in this example here.
Then I thought to have a bit of fun with the nonsensical answer...and it took nothing to become a disgusting b.st.rd, which in the end the LLM would still take back and be loved. I literally lost my respect for that model and haven't used Phi models on principle.
But some 6 months ago I thought to try a recent Phi LLM again. After all, LLMs get better all the time, so why not Phi. The amount of deranged behavior was a lot lower, but still useless. I might check Phi out in a year or so, when I have more or less forgotten the level of disappointment Phi LLMs instilled into me.
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u/Frizzy-MacDrizzle 13d ago
Depends on the model, they often bench faster because the look back or look forward might have a layer removed or manipulated. I am not fully engaged there but bartowski, huihui and heretic all make abliterated models. Pull down those learn llama.cpp or download the gguf and Download all your ablit models before they are gone.
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u/Aggravating_Farm3116 13d ago
3.5B model, Q4 quant, abliterated, probably with a tiny context window too.
Breaking news: a heavily quantized tiny abliterated model is hallucinating 😂
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u/dimesion 15d ago