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write readme (benchmarks are running as we speak)
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README.md
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---
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license: mit
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tags:
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- phi3
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- nlp
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- moe
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datasets:
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- BEE-spoke-data/gutenberg-en-v1-clean
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- NeelNanda/pile-10k
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---
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# phi 3 4x4b
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a continually pretrained phi3-mini sparse moe upcycle
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## support me on ko-fi!
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[~~please i need money to stay alive and keep making models~~](https://ko-fi.com/fizzai)
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## notes
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*not trained on instruct data.* it's pretty likely that it won't be much different from phi 3 if you use it like that, if not worse due to any forgetting of instruct formats during the continued training.
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## future experiments
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- the datasets for this were literally chosen on a whim. perhaps experiment with a highly filtered [HuggingFaceFW/fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu)?
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- actually freeze the gate layers next time (see [Chen et. al, 2023](https://arxiv.org/abs/2303.01610)), oops
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- MOAR TRAINING, this only went up to ~0.2 of an epoch because i ran out of dolar
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