Automatic Speech Recognition
Safetensors
GGUF
VibeVoice
ggml
ASR
quantization
cpu-inference
bitnet
multilingual
conversational
Instructions to use microsoft/VibeVoice-ASR-BitNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use microsoft/VibeVoice-ASR-BitNet with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="microsoft/VibeVoice-ASR-BitNet", filename="vibeasr-lm-i2_s-embed-q6_k.gguf", )
llm.create_chat_completion( messages = "\"sample1.flac\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use microsoft/VibeVoice-ASR-BitNet 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 microsoft/VibeVoice-ASR-BitNet:Q6_K # Run inference directly in the terminal: llama cli -hf microsoft/VibeVoice-ASR-BitNet:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf microsoft/VibeVoice-ASR-BitNet:Q6_K # Run inference directly in the terminal: llama cli -hf microsoft/VibeVoice-ASR-BitNet:Q6_K
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 microsoft/VibeVoice-ASR-BitNet:Q6_K # Run inference directly in the terminal: ./llama-cli -hf microsoft/VibeVoice-ASR-BitNet:Q6_K
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 microsoft/VibeVoice-ASR-BitNet:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf microsoft/VibeVoice-ASR-BitNet:Q6_K
Use Docker
docker model run hf.co/microsoft/VibeVoice-ASR-BitNet:Q6_K
- LM Studio
- Jan
- Ollama
How to use microsoft/VibeVoice-ASR-BitNet with Ollama:
ollama run hf.co/microsoft/VibeVoice-ASR-BitNet:Q6_K
- Unsloth Studio
How to use microsoft/VibeVoice-ASR-BitNet 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 microsoft/VibeVoice-ASR-BitNet 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 microsoft/VibeVoice-ASR-BitNet to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for microsoft/VibeVoice-ASR-BitNet to start chatting
- Atomic Chat new
- Docker Model Runner
How to use microsoft/VibeVoice-ASR-BitNet with Docker Model Runner:
docker model run hf.co/microsoft/VibeVoice-ASR-BitNet:Q6_K
- Lemonade
How to use microsoft/VibeVoice-ASR-BitNet with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull microsoft/VibeVoice-ASR-BitNet:Q6_K
Run and chat with the model
lemonade run user.VibeVoice-ASR-BitNet-Q6_K
List all available models
lemonade list
File size: 1,289 Bytes
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"add_prefix_space": false,
"added_tokens_decoder": {
"151643": {
"content": "<|endoftext|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"151644": {
"content": "<|im_start|>",
"lstrip": false,
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"rstrip": false,
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"151645": {
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"special": true
}
},
"additional_special_tokens": ["<|im_start|>", "<|im_end|>"],
"bos_token": null,
"chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"errors": "replace",
"model_max_length": 32768,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
}
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