---
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-135M-Instruct
pipeline_tag: text-generation
tags:
  - safetensors
  - study-assistant
  - fine-tuned
---

# 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.