docs: add project documentation and voice cloning notice
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config/voxcpm2-a10.yaml
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54
config/voxcpm2-a10.yaml
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# VoxCPM2 deploy: single-stage AR pipeline with per-request state batching.
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# Runs on large (H20 141GB) and small (24GB L4) cards alike: the KV cache is
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# pinned to a right-sized budget instead of ballooning to fill the card.
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#
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# VoxCPM2-local runtime knobs are passed through hf_overrides.
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async_chunk: false
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dtype: bfloat16
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stages:
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- stage_id: 0
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custom_voice_dir: /home/opc/voxcpm-vllm-poc/runtime/voices
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max_num_seqs: 2
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#max_num_seqs: 8
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gpu_memory_utilization: 0.9
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# Right-size the KV cache instead of letting it fill gpu_memory_utilization.
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# max_num_seqs(8) * max_model_len(4096) ~= 32k tokens; 6 GiB leaves headroom
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# for longer live requests while keeping VoxCPM2 TTS decode batches small
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# enough to avoid the high ITL observed with large admission caps.
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# The remaining VRAM stays free for the VoxCPM2 diffusion side-path
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# (LocDiT / AudioVAE / code2wav + batch CUDA-graph pools), which allocates
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# outside vLLM's KV accounting during inference. Keeps peak ~13 GiB on any
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# card and avoids per-rebase OOM tuning on small CI GPUs.
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# Assumes prefix caching off and typical live decode concurrency <= ~8;
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# raise this cap if either grows or enable_prefix_caching is turned on.
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kv_cache_memory_bytes: 6442450944 # 6 GiB
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enforce_eager: true
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trust_remote_code: true
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enable_prefix_caching: false
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async_scheduling: true
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max_num_batched_tokens: 4096
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max_model_len: 4096
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devices: "0"
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engine_extras:
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hf_overrides:
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voxcpm2_runtime_config:
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audio_emit_every: 1
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vae_decode_every: 3
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enable_batched_cfm: true
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enable_batched_vae_decode: true
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coalesce_audio_d2h: true
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enable_loc_dit_fused_qkv: true
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enable_loc_dit_fused_mlp: true
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enable_loc_dit_zero_dt_cache: true
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enable_loc_dit_skip_qkv_contig: true
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enable_loc_dit_reduce_overhead_no_cg: true
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enable_unified_decode_graph: true
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unified_decode_graph_max_batch_size: 8
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default_sampling_params:
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temperature: 0.0
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top_p: 1.0
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top_k: -1
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max_tokens: 4096
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seed: 42
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repetition_penalty: 1.0
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