metadata
language:
- en
- vi
license: other
library_name: gguf
tags:
- acne
- dermatology
- skincare
- gguf
- qwen3.5
- bilingual
pipeline_tag: text-generation
base_model:
- Qwen/Qwen3.5-0.8B
Acnoryx AI Release
Overview
- Model family: Qwen/Qwen3.5-0.8B
- Project name: acnoryx
- Model size: 0.8b
- GGUF quantizations: F16, Q8_0, Q5_K_M, Q4_K_M, Q4_0, IQ4_NL, IQ4_XS
- Domain: acne, acne-prone skin, skincare, and dermatology guidance
App
Default behavior
- The saved tokenizer/chat template injects a short default system prompt when no system message is provided.
- That means the model can still understand its identity as Acnoryx AI in chat mode without a long system prompt.
- For best results, write Vietnamese with full accents, or use natural English.
Prompt examples
- Tiếng Việt:
Da em nhiều mụn viêm ở má, routine hiện tại chỉ có sữa rửa mặt và kem dưỡng. Em nên ưu tiên gì trước? - Tiếng Việt:
Kết quả quét của tôi có mụn đầu đen 32%, mụn mủ 21%, thâm mụn 18%. Hãy tóm tắt đúng theo dữ liệu. - English:
I have oily acne-prone skin with dark marks after breakouts. What should I prioritize first?
Included folders
- gguf/: GGUF exports for llama.cpp runtimes
- hf_transformers/: merged Hugging Face Transformers model
Training stack
- Transformers + PEFT + TRL bf16 LoRA
- Qwen3.5 hybrid architecture with fast linear path enabled when available
Prompting
- See PROMPT_TEMPLATE.txt for usage guidance.
Evaluation Snapshot
Release GGUFs were retested on the curated release_eval_v1 set with 58 bilingual questions in both thinking and non-thinking modes.
| Quant | Think | No-Think | Avg | Notes |
|---|---|---|---|---|
| Q8_0 | 86.2% | 87.9% | 87.0% | Best overall score in the current release rerun |
| Q5_K_M | 89.7% | 82.8% | 86.2% | Strong think-mode quality |
| IQ4_NL | 86.2% | 86.2% | 86.2% | Best balanced sub-500 MB option |
| F16 | 87.9% | 81.0% | 84.4% | Highest-fidelity source export |
| IQ4_XS | 84.5% | 81.0% | 82.8% | Smaller release option |
| Q4_K_M | 82.8% | 81.0% | 81.9% | Usable but clearly weaker than Q8_0 / Q5_K_M |
| Q4_0 | 77.6% | 75.9% | 76.8% | Lowest-quality release quant |
Deployment Guidance
- Recommended default release quant: Q8_0
- Best size/quality trade-off under 500 MB: IQ4_NL
- Keep Q4_0 only for constrained experiments, not as a primary deployment target
- Current release family remains below the older internal 96% gate, so these artifacts should be treated as interim bundles rather than a final quality-signoff build
Test Results
Latest automated GGUF test results are below:
- acnoryx-0.8b-f16: Think mode 87.9%, No-Think mode 81.0%
- acnoryx-0.8b-iq4_nl: Think mode 86.2%, No-Think mode 86.2%
- acnoryx-0.8b-iq4_xs: Think mode 84.5%, No-Think mode 81.0%
- acnoryx-0.8b-q4_0: Think mode 77.6%, No-Think mode 75.9%
- acnoryx-0.8b-q4_k_m: Think mode 82.8%, No-Think mode 81.0%
- acnoryx-0.8b-q5_k_m: Think mode 89.7%, No-Think mode 82.8%
- acnoryx-0.8b-q8_0: Think mode 86.2%, No-Think mode 87.9%
Full detailed results in results/release_gguf_0.8b/TEST_RESULTS.json.
For cross-family comparison with research quants, see results/COMPARISON.md in the workspace.