ProfessorF is Nick V. Flor, PhD
Models quantized for research reproducibility purposes
Trinity Nano Preview GGUF
Trinity Nano Preview is a preview of Arcee AI's 6B MoE model with 1B active parameters. It is the small-sized model in our new Trinity family, a series of open-weight models for enterprise and tinkerers alike.
This is a chat tuned model, with a delightful personality and charm we think users will love. We note that this model is pushing the limits of sparsity in small language models with only 800M non-embedding parameters active per token, and as such
may be unstable
in certain use cases, especially in this preview.
This is an
experimental
release, it's fun to talk to but will not be hosted anywhere, so download it and try it out yourself!
These are the GGUF files for running on llama.cpp powered platforms
Trinity Nano Preview is trained on 10T tokens gathered and curated through a key partnership with
Datology
, building upon the excellent dataset we used on
AFM-4.5B
with additional math and code.
Training was performed on a cluster of 512 H200 GPUs powered by
Prime Intellect
using HSDP parallelism.
More details, including key architecture decisions, can be found on our blog
here
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