# AUTARCH LLM Configuration Template
# Hardware: Orange Pi 5 Plus (RK3588 SoC, 8-core ARM, 16GB RAM)
# Optimized for: CPU-only inference on ARM64
#
# This configuration is optimized for the Orange Pi 5 Plus running
# CPU-only inference. The RK3588 has 4x Cortex-A76 + 4x Cortex-A55 cores.
# Best with quantized GGUF models (Q4_K_M or Q5_K_M).

[llama]
# GGUF Model Settings (llama.cpp)
# Recommended: Use Q4_K_M or Q5_K_M quantized models
model_path =
n_ctx = 2048
n_threads = 4
n_gpu_layers = 0
temperature = 0.7
top_p = 0.9
top_k = 40
repeat_penalty = 1.1
max_tokens = 1024
seed = -1

[transformers]
# SafeTensors Model Settings (HuggingFace)
# Note: CPU inference is slow with transformers, GGUF recommended
model_path =
device = cpu
torch_dtype = float32
load_in_8bit = false
load_in_4bit = false
trust_remote_code = false
max_tokens = 1024
temperature = 0.7
top_p = 0.9
top_k = 40
repetition_penalty = 1.1

# Notes:
# - n_threads = 4 uses only the fast A76 cores (better perf than all 8)
# - n_ctx = 2048 balances memory usage and capability
# - n_gpu_layers = 0 for pure CPU inference
# - Strongly recommend GGUF Q4_K_M models for best speed
# - 7B Q4 models use ~4GB RAM, leaving room for system
# - max_tokens = 1024 keeps generation times reasonable
# - For transformers: CPU with float32 is slow but works
# - Avoid 13B+ models unless heavily quantized
