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Termux-Diffusion

v1.1.1 (Dual Engine)
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Model Hub & GGUF Quantization Presets

Specifications for built-in mobile-optimized presets and custom weight resolution.

Preset Name Base Architecture & Quantization File Size Optimal Steps & CFG Recommended Sampler Key Visual Workload
"sdxs" SDXS 512 Tiny SD Distilled (Q8_0) 651 MB 1 ~ 2 steps (CFG 1.0) euler_a Ultra-low latency mobile prototyping (Instant 1-2s, sharp)
"anime" DreamShaper 8 LCM (Q4_0) 1.55 GB 4 ~ 8 steps (CFG 1.5) lcm 2D / 2.5D stylized anime art (Crisp lineart, rich cel-shading)
"realistic" Realistic Vision V6.0 B1 (Q4_K) 1.55 GB 20 ~ 25 steps (CFG 7.0) dpm2 / karras Ultra-detailed photorealism (Pores, eyes, cinematic lighting)
"speed" Stable Diffusion 1.5 Base (Q4_1) 1.68 GB 15 ~ 20 steps (CFG 6.0) euler_a / dpm++2m General-purpose drafting and balanced composition
"turbo" Stable Diffusion 1.5 Pruned (Q4_0) 1.49 GB 15 ~ 20 steps (CFG 6.0) euler_a / dpm++2m Lightweight SD1.5 base generation
💡 Denoising Architecture Rules (ė •ė„ 파ëŧ미터 ę°€ė´ë“œ)

1. Distilled Models (sdxs, anime): Keep CFG low (1.0~1.5) and use 1st-order samplers (euler_a, lcm). High CFG or 2nd-order ODE samplers (dpm2) will collapse the latent space.

2. Full SD1.5 Models (realistic, speed, turbo): Require at least 15~20 steps and CFG 6.0~7.5 with quality-guard negative prompts to fully resolve photorealistic details.

Custom Model Management API

from termux_diffusion import (
    set_cache_dir,       # Route cache to external storage / SD card
    get_cache_dir,       # Inspect active cache directory
    download_model,      # Pre-download models in background with progress
    register_model,      # Register custom Hugging Face GGUF models
    list_cached_models,  # Inspect downloaded models
    clear_cache          # Purge cache to reclaim storage
)

# 1. Configure custom cache storage path (e.g. SD Card)
set_cache_dir("~/storage/external-1/ai_models")

# 2. Pre-fetch preset weights
download_model("sdxs", force=False)

# 3. Register custom repository alias
register_model(
    name="waifu",
    repo_id="second-state/DreamShaper-8-GGUF",
    filename="dreamshaper-8-Q4_k.gguf",
    description="DreamShaper 8 Q4_K model for stylized anime portraits"
)

# 4. View cached weights
models = list_cached_models()
for m in models:
    print(f"Model: {m['name']}, Size: {m['size_mb']:.1f}MB")