Automatic Speech Recognition
GGUF
VibeVoice
ggml
ASR
quantization
cpu-inference
bitnet
conversational
Instructions to use P2Enjoy/VibeVoice-ASR-BitNet-slim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use P2Enjoy/VibeVoice-ASR-BitNet-slim with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf P2Enjoy/VibeVoice-ASR-BitNet-slim # Run inference directly in the terminal: llama cli -hf P2Enjoy/VibeVoice-ASR-BitNet-slim
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf P2Enjoy/VibeVoice-ASR-BitNet-slim # Run inference directly in the terminal: llama cli -hf P2Enjoy/VibeVoice-ASR-BitNet-slim
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf P2Enjoy/VibeVoice-ASR-BitNet-slim # Run inference directly in the terminal: ./llama-cli -hf P2Enjoy/VibeVoice-ASR-BitNet-slim
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf P2Enjoy/VibeVoice-ASR-BitNet-slim # Run inference directly in the terminal: ./build/bin/llama-cli -hf P2Enjoy/VibeVoice-ASR-BitNet-slim
Use Docker
docker model run hf.co/P2Enjoy/VibeVoice-ASR-BitNet-slim
- LM Studio
- Jan
- Ollama
How to use P2Enjoy/VibeVoice-ASR-BitNet-slim with Ollama:
ollama run hf.co/P2Enjoy/VibeVoice-ASR-BitNet-slim
- Unsloth Studio
How to use P2Enjoy/VibeVoice-ASR-BitNet-slim with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for P2Enjoy/VibeVoice-ASR-BitNet-slim to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for P2Enjoy/VibeVoice-ASR-BitNet-slim to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for P2Enjoy/VibeVoice-ASR-BitNet-slim to start chatting
- Docker Model Runner
How to use P2Enjoy/VibeVoice-ASR-BitNet-slim with Docker Model Runner:
docker model run hf.co/P2Enjoy/VibeVoice-ASR-BitNet-slim
- Lemonade
How to use P2Enjoy/VibeVoice-ASR-BitNet-slim with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull P2Enjoy/VibeVoice-ASR-BitNet-slim
Run and chat with the model
lemonade run user.VibeVoice-ASR-BitNet-slim-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
File size: 3,527 Bytes
a1d788f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 | {
"_attn_implementation_autoset": false,
"acoustic_tokenizer_config": {
"causal": true,
"channels": 1,
"conv_bias": true,
"conv_norm": "none",
"corpus_normalize": 0.0,
"decoder_depths": null,
"decoder_n_filters": 32,
"decoder_ratios": [
8,
5,
5,
4,
2,
2
],
"disable_last_norm": true,
"dtype": "bfloat16",
"encoder_depths": "3-3-3-3-3-3-8",
"encoder_n_filters": 32,
"encoder_ratios": [
8,
5,
5,
4,
2,
2
],
"fix_std": 0.5,
"layer_scale_init_value": 1e-06,
"layernorm": "RMSNorm",
"layernorm_elementwise_affine": true,
"layernorm_eps": 1e-05,
"mixer_layer": "depthwise_conv",
"model_type": "vibevoice_acoustic_tokenizer",
"pad_mode": "constant",
"std_dist_type": "gaussian",
"vae_dim": 64,
"weight_init_value": 0.01
},
"acoustic_vae_dim": 64,
"architectures": [
"VibeVoiceForASRTraining"
],
"decoder_config": {
"attention_dropout": 0.0,
"dtype": "bfloat16",
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"layer_types": [
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention"
],
"max_position_embeddings": 65536,
"max_window_layers": 28,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000.0,
"sliding_window": null,
"tie_word_embeddings": true,
"use_cache": true,
"use_sliding_window": false,
"vocab_size": 151936
},
"diffusion_head_config": {
"ddpm_batch_mul": 4,
"ddpm_beta_schedule": "cosine",
"ddpm_num_inference_steps": 20,
"ddpm_num_steps": 1000,
"diffusion_type": "ddpm",
"head_ffn_ratio": 3.0,
"head_layers": 4,
"hidden_size": 1536,
"latent_size": 64,
"model_type": "vibepod_diffusion_head",
"prediction_type": "v_prediction",
"rms_norm_eps": 1e-05,
"speech_vae_dim": 64
},
"dtype": "float32",
"model_type": "vibevoice",
"semantic_tokenizer_config": {
"causal": true,
"channels": 1,
"conv_bias": true,
"conv_norm": "none",
"corpus_normalize": 0.0,
"disable_last_norm": true,
"dtype": "bfloat16",
"encoder_depths": "3-3-3-3-3-3-8",
"encoder_n_filters": 32,
"encoder_ratios": [
8,
5,
5,
4,
2,
2
],
"fix_std": 0,
"layer_scale_init_value": 1e-06,
"layernorm": "RMSNorm",
"layernorm_elementwise_affine": true,
"layernorm_eps": 1e-05,
"mixer_layer": "depthwise_conv",
"model_type": "vibevoice_semantic_tokenizer",
"pad_mode": "constant",
"std_dist_type": "none",
"vae_dim": 128,
"weight_init_value": 0.01
},
"semantic_vae_dim": 128,
"transformers_version": "4.57.6"
}
|