wyzer-2.0-smollm2-135m

Wyzer 2.0 (SmolLM2-135M fine-tune)

The conversational companion inside the BackOnTrack study app. LoRA fine-tune of SmolLM2-135M-Instruct, merged to native Transformers format (safetensors) — this is the deployment artifact served by the Wyzer FastAPI Space. An optional wyzer-2.0-q4_k_m.gguf is included for local llama.cpp inference. The 135M size was chosen deliberately: it trains on a laptop CPU and responds fast on Hugging Face's free 2-vCPU tier.

Trained behaviours:

• Grounded answers: user metrics arrive in a [CONTEXT]...[/CONTEXT] block; the model quotes numbers only from there.
• Refusal to fabricate: missing data → says so instead of guessing.
• Action honesty: recommends, never claims to execute; the app's deterministic engine performs approved actions.
• Mentor persona across study, tech, career, fitness, wellbeing (English + Hinglish).

Trained offline with a synthetic instruction dataset (~900 examples, 2 epochs, LoRA r=16). Not a general-purpose assistant; expect app-domain behaviour.