Acnoryx / Airy

Acnoryx/Airy GGUFs

GGUF pack for the fine-tuned Acnoryx acne-care assistant model, prepared for direct publishing under Acnoryx/Airy .

• Hugging Face repo: Acnoryx/Airy
• Product app: Acnoryx - AI for Acne Care

Important scope

This repo is a research snapshot : it explores how far the model can be compressed while still keeping acceptable acne-domain quality.

It is not the production model used inside the Acnoryx app; the app may use different quantization, prompt format, runtime settings, and evaluation criteria.

What this repo contains

This repo focuses on a small set of high-value research GGUFs for Acnoryx/Airy. The most important published candidates are listed in the evaluation table below.

Model Quality Summary

The tables below group the models by practical quality. Models with <50% thinking accuracy are separated into a “Low-quality / not recommended” section so the “Core + Airy” table stays focused on the usable candidates.

Core (release floor)

Airy candidates (acceptable quality)

Low-quality / not recommended (thinking < 50%)

These models are included for transparency but are not recommended for deployment due to very low thinking accuracy.

Key Takeaways

Recommendations

How To Run

1. Install Python packages

pip install huggingface_hub llama-cpp-python

huggingface_hub is used to download the GGUF file from Hugging Face.

llama-cpp-python is used to actually load and run the GGUF model in Python.

2. Download a GGUF from Hugging Face in Python

from huggingface_hub import hf_hub_download

model_path = hf_hub_download(
  repo_id="Acnoryx/Airy",
  filename="airy-iq3_s.gguf",
  local_dir="gguf",
)

print(model_path)

3. Run inference in Python

from huggingface_hub import hf_hub_download
from llama_cpp import Llama

model_path = hf_hub_download(
  repo_id="Acnoryx/Airy",
  filename="airy-iq3_s.gguf",
  local_dir="gguf",
)

llm = Llama(
  model_path=model_path,
  n_ctx=4096,
  n_gpu_layers=-1,
  verbose=False,
)

result = llm.create_chat_completion(
  messages=[
    {"role": "system", "content": "You are Acnoryx AI, a dermatology assistant focused on acne and skincare."},
    {"role": "user", "content": "What are blackheads?"},
  ],
  temperature=0.2,
)

print(result["choices"][0]["message"]["content"])

4. Swap model files quickly

Just change the filename value:

• airy-iq3_s.gguf
• airy-q2_k.gguf
• airy-iq2_s.gguf

5. Quick pick guide

• Choose airy-iq3_s.gguf for the strongest overall result.
• Choose airy-q2_k.gguf for the best compression/value balance.
• Choose airy-iq2_s.gguf only if you need a much smaller file and can accept a visible quality drop.

Final Conclusion

The current Airy lineup proves that the model can go below the old release-floor size while still keeping strong acne-domain quality.

The best files in this repo are:

• airy-iq3_s.gguf
• airy-iq3_xs.gguf
• airy-q2_k.gguf
• airy-q2_k_s.gguf

Among them, airy-iq3_s.gguf is the safest default publish choice, while airy-q2_k.gguf is the best efficiency result.