elythros-decider-0.6b-GGUF
A GGUF build of elythros-decider-0.6b, for running typed decisions on llama.cpp instead of a hosted API.
Community card
What this is
A repackaged build of elythros-decider-0.6b, not a separate model. The weights are the same; what changes is the runtime you can put them in and the hardware that will hold them.
Its card lists training data: PolyAI/banking77, clinc/clinc_oos, nyu-mll/glue, stanfordnlp/snli, google/boolq, stanfordnlp/sst2, cais/mmlu. That matters when you read any benchmark number about it, because a model tuned on a benchmark's own training split has an advantage over one that has never seen it.
How to run it
llama.cpp
GGUF runs on CPU. No Python, no GPU, and no network call in the path of a decision. Full llama.cpp guide.
llama-cli -hf mradermacher/elythros-decider-0.6b-GGUFMLX on Apple Silicon
MLX uses the unified memory on M-series chips, which is the fastest local option on a Mac. Full MLX on Apple Silicon guide.
mlx_lm.generate --model mradermacher/elythros-decider-0.6b-GGUFA public number is a shortlist, not a decision
The only benchmark that settles which model you ship is one built from your own historical decisions. We freeze that test set, run the candidates against it, and hand back the threshold your error budget supports.