GhostAI_LiquidSFT-v2

GhostAI_LiquidSFT v2 (full fine-tune)

On-device Solana wallet assistant — a full-weight fine-tune of LFM2.5-1.2B for mobile inference (llama.cpp / llama.rn). v2 improves on the v1 LoRA model with a larger, teacher-augmented + cleaned dataset.

What's new vs v1

• Full-weight fine-tune (8-GPU DDP) instead of LoRA → eval_loss 0.1534 (v1 LoRA: 0.1736)
• Dataset grown to ~78k cleaned rows via grounded augmentation (Qwen3.6 teacher + Google-grounded Solana facts), with: tool-error recovery, multi-step chains, clarification on high-stakes asks, follow-ups, hard negatives, and Ghost AI identity.
• Every tool-call validated against the 172-tool schema; tool args grounded in context (no hallucinated addresses).

Held-out evaluation

Files

⚠️ Serving note (important)

This model is trained train==serve with the on-device tool-catalog system prompt. Always send that catalog as the system message — with an ad-hoc system prompt, tool-calling degrades. Tool calls use Hermes format: <tool_call>{"name":...,"arguments":{...}}</tool_call>.

Training

LFM2.5-1.2B-Instruct base · full fine-tune · lr 1e-5 · 2 epochs · eff-batch 256 · bf16 · completion_only_loss (user/tool turns masked) · seq 2048 (0% truncation).