2-5x faster 50% less memory local LLM finetuning

• Manual autograd engine - hand derived backprop steps.


• 2x to 5x faster than QLoRA. 50% less memory usage.


• All kernels written in OpenAI's Triton language.


• 0% loss in accuracy - no approximation methods - all exact.


• No change of hardware necessary. Supports NVIDIA GPUs since 2018+. Minimum CUDA Compute Cap

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This dataset is an attempt to replicate the results of Microsoft's Orca

Our dataset consists of:

~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)

~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)

We followed the submix and system prompt distribution outlined in the Orca pape... See more