# MOSS-TTS-Delay — llama.cpp Backend (CPU-only)
#
# For machines without GPU.  All computation runs on CPU.
# Performance will be slower but no CUDA/GPU drivers required.
#
# Installation:
#   pip install -e ".[llama-cpp]"
#   pip install onnxruntime    # CPU-only ONNX Runtime

# ── Model paths ──────────────────────────────────────────────────────────────

backbone_gguf: weights/MOSS-TTS-GGUF/MOSS_TTS_Q4_K_M.gguf
embedding_dir: weights/MOSS-TTS-GGUF/embeddings
lm_head_dir: weights/MOSS-TTS-GGUF/lm_heads
tokenizer_dir: weights/MOSS-TTS-GGUF/tokenizer

# ── Audio tokenizer ──────────────────────────────────────────────────────────

audio_backend: onnx
audio_encoder_onnx: weights/MOSS-Audio-Tokenizer-ONNX/encoder.onnx
audio_decoder_onnx: weights/MOSS-Audio-Tokenizer-ONNX/decoder.onnx

# ── LM heads backend ────────────────────────────────────────────────────────

heads_backend: numpy

# ── Runtime settings ─────────────────────────────────────────────────────────

n_ctx: 4096
n_batch: 256
n_threads: 8
n_gpu_layers: 0
max_new_tokens: 3072
use_gpu_audio: false

# ── Sampling parameters ──────────────────────────────────────────────────────

text_temperature: 1.5
text_top_p: 1.0
text_top_k: 50

audio_temperature: 1.7
audio_top_p: 0.8
audio_top_k: 25
audio_repetition_penalty: 1.0
