LocalLLaMA

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is the 4k context length of llama2 for real? (self.localllama)

submitted 2 years ago by actuallyacat to c/localllama

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I've been using airoboros-l2-70b for writing fiction, and while overall I'd describe the results as excellent and better than any llama1 model I've used, it doesn't seem to be living up to the promise of 4k token sequence length.

Around 2500 tokens output quality degrades rapidly, and either starts repeating previous text verbatim, or becomes incoherent (grammar, punctuation and capitalization disappear, becomes salad of vaguely related words)

Any other experiences with llama2 and long context? Does the base model work better? Are other fine tunes behaving similarly? I'll try myself eventually, but the 70b models are chunky downloads, and experimentation takes a while at 1 t/s.

(I'm using GGML Q4_K_M on kobold.cpp, with rope scaling off like you're supposed to do with llama2)

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[–] actuallyacat 3 points 2 years ago* (last edited 2 years ago)

You are supposed to manually set scale to 1.0 and base to 10000 when using llama 2 with 4096 context. The automatic scaling assumes the model was trained for 2048. Though as I say in the OP, that still doesn't work, at least with this particular fine tune.