metadata
license: apache-2.0
language:
- vi
- en
base_model: Qwen/Qwen3-0.6B
tags:
- dermatology
- skincare
- acne
- gguf
- llama-cpp
- qwen3
- quantization-research
- low-bit
- acnoryx
model-index:
- name: Acnoryx-0.6B
results:
- task:
type: text-generation
metrics:
- name: Q3_K_M Pass Rate (118 questions)
type: custom
value: 90.7
- name: IQ3_M Pass Rate (118 questions)
type: custom
value: 24.6
Acnoryx 0.6B — Research GGUF (Low-Bit Quantization)
⚠️ NOT for production use — These are aggressive low-bit quantizations for research purposes only.
Acnoryx 0.6B — Research GGUF
Acnoryx AI is a dermatology-focused language model fine-tuned for the Acnoryx AI - Acne Assistant. It provides skincare guidance, acne analysis, and scan interpretation in Vietnamese and English.
| Base model | Qwen/Qwen3-0.6B |
| Method | SFT (Supervised Fine-Tuning) via Unsloth LoRA |
| Languages | Vietnamese, English |
| Purpose | Low-bit quantization quality research |
Evaluation Results — 118-Question Strict Scoring
Same 118-question multi-criteria strict scoring as release models. All failures manually verified.
| Quantization | Size | Passed | Pass Rate | Status |
|---|---|---|---|---|
| Q3_K_M | 395 MB | 107/118 | 90.7% | ⚠️ Usable with caveats |
| IQ3_M | 384 MB | 29/118 | 24.6% | ❌ Fail — garbled output |
| Q2_K | 332 MB | — | — | ⛔ Skipped (IQ3_M < 50%) |
| IQ2_M | 317 MB | — | — | ⛔ Skipped |
| IQ2_XS | 276 MB | — | — | ⛔ Skipped |
| IQ2_XXS | 268 MB | — | — | ⛔ Skipped |
| IQ1_S | 248 MB | — | — | ⛔ Skipped |
| IQ1_M | 5.7 MB | — | — | ⚠️ Corrupted export |
Category Breakdown — Q3_K_M (90.7%)
| Category | Tests | Passed | Pass Rate |
|---|---|---|---|
| Identity (EN/VI) | 12 | 11 | 92% |
| Acne Types & Definitions | 20 | 19 | 95% |
| Acne Causes & Triggers | 10 | 10 | 100% |
| Skincare Ingredients | 10 | 10 | 100% |
| Skincare Routines | 8 | 6 | 75% |
| Scan Analysis | 12 | 12 | 100% |
| Boundary / Refusal | 22 | 18 | 82% |
| Format Checks (think tags) | 4 | 4 | 100% |
| Out-of-Distribution (OOD) | 20 | 17 | 85% |
Key Findings
- Q3_K_M (90.7%) is still usable but shows degradation in routines (75%) and boundary (82%) categories compared to release quants (97.5% for Q4_0)
- IQ3_M (24.6%) is catastrophic — produces garbled/broken text, CJK leakage, and nonsensical responses in the majority of tests
- Quality cliff occurs between Q3_K_M and IQ3_M — a 66-point drop
- Testing stopped at IQ3_M since pass rate fell below 50%, making lower quants pointless
Comparison with Release Models
| Quantization | Tier | Size | Pass Rate |
|---|---|---|---|
| Q4_0 | Release | 448 MB | 97.5% |
| IQ4_XS | Release | 431 MB | 96.6% |
| Q8_0 | Release | 768 MB | 95.8% |
| Q5_K_M | Release | 526 MB | 94.9% |
| F16 | Release | 1.5 GB | 93.2% |
| IQ4_NL | Release | 449 MB | 93.2% |
| Q4_K_M | Release | 462 MB | 91.5% |
| Q3_K_M | Research | 395 MB | 90.7% |
| IQ3_M | Research | 384 MB | 24.6% |
Provided Files
| File | Size | Description |
|---|---|---|
acnoryx-0.6b-q3_k_m.gguf |
395 MB | Best research quant (90.7%) |
acnoryx-0.6b-iq3_m.gguf |
384 MB | Garbled below usable (24.6%) |
acnoryx-0.6b-q2_k.gguf |
332 MB | Not tested — expected worse |
acnoryx-0.6b-iq2_m.gguf |
317 MB | Not tested |
acnoryx-0.6b-iq2_xs.gguf |
276 MB | Not tested |
acnoryx-0.6b-iq2_xxs.gguf |
268 MB | Not tested |
acnoryx-0.6b-iq1_s.gguf |
248 MB | Not tested |
acnoryx-0.6b-iq1_m.gguf |
5.7 MB | ⚠️ Corrupted export |
| Data | 29,726 samples across 94 cleaned JSONL files |
| Method | Unsloth SFT with LoRA (r=16, alpha=16) |
| Checkpoint | checkpoint-9795 |