Instructions to use addyo07/vox-models 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 addyo07/vox-models 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 addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: llama cli -hf addyo07/vox-models:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: llama cli -hf addyo07/vox-models:Q4_K_M
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 addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf addyo07/vox-models:Q4_K_M
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 addyo07/vox-models:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf addyo07/vox-models:Q4_K_M
Use Docker
docker model run hf.co/addyo07/vox-models:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use addyo07/vox-models with Ollama:
ollama run hf.co/addyo07/vox-models:Q4_K_M
- Unsloth Studio
How to use addyo07/vox-models 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 addyo07/vox-models 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 addyo07/vox-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for addyo07/vox-models to start chatting
- Pi
How to use addyo07/vox-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf addyo07/vox-models:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "addyo07/vox-models:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use addyo07/vox-models with Docker Model Runner:
docker model run hf.co/addyo07/vox-models:Q4_K_M
- Lemonade
How to use addyo07/vox-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull addyo07/vox-models:Q4_K_M
Run and chat with the model
lemonade run user.vox-models-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use addyo07/vox-models with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf addyo07/vox-models:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default addyo07/vox-models:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use addyo07/vox-models with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf addyo07/vox-models:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "addyo07/vox-models:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
addy-hypr4 commited on
Commit ·
b536905
1
Parent(s): 2f0c401
Standardize model asset paths and update models manifest
Browse files- embedding/minilm-l12-v2/README.md +3 -0
- embedding/minilm-l12-v2/config.json +3 -0
- embedding/minilm-l12-v2/model_int8.onnx +3 -0
- embedding/minilm-l12-v2/special_tokens_map.json +3 -0
- embedding/minilm-l12-v2/tokenizer.json +3 -0
- embedding/minilm-l12-v2/tokenizer_config.json +3 -0
- embedding/minilm-l12-v2/unigram.json +3 -0
- llm/gemma4/{google_gemma-4-E2B-it-Q4_K_M.gguf → gemma-4-e2b-q4_k_m.gguf} +0 -0
- llm/llama/{Llama-3.2-1B-Instruct-Q4_K_M.gguf → llama-3.2-1b-q4_k_m.gguf} +0 -0
- llm/llama/{Llama-3.2-1B-Instruct-Q6_K.gguf → llama-3.2-1b-q6_k.gguf} +0 -0
- models_manifest.json +40 -32
- nli/{deberta-v3-xsmall-nli → deberta-v3-xsmall}/model_quantized.onnx +0 -0
- nli/{deberta-v3-xsmall-nli → deberta-v3-xsmall}/tokenizer.json +0 -0
- stt/{nvidia-nemotron-3.5 → nemotron-3.5}/config.json +0 -0
- stt/{nvidia-nemotron-3.5 → nemotron-3.5}/decoder_joint.onnx +0 -0
- stt/{nvidia-nemotron-3.5 → nemotron-3.5}/encoder.onnx +0 -0
- stt/{nvidia-nemotron-3.5 → nemotron-3.5}/tokenizer.model +0 -0
- tts/chatterbox/{chatterbox-s3gen-mtl-f16.gguf → s3gen-f16.gguf} +0 -0
- tts/chatterbox/{chatterbox-t3-mtl-q4_0.gguf → t3-q4_0.gguf} +0 -0
embedding/minilm-l12-v2/README.md
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llm/gemma4/{google_gemma-4-E2B-it-Q4_K_M.gguf → gemma-4-e2b-q4_k_m.gguf}
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llm/llama/{Llama-3.2-1B-Instruct-Q4_K_M.gguf → llama-3.2-1b-q4_k_m.gguf}
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llm/llama/{Llama-3.2-1B-Instruct-Q6_K.gguf → llama-3.2-1b-q6_k.gguf}
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models_manifest.json
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"sha256": "6f85a640a97cf2bf5b8e764087b1e83da0fdb51d7c9fab7d0fece9385611df83",
|
| 174 |
"required": false
|
|
|
|
| 183 |
"files": [
|
| 184 |
{
|
| 185 |
"id": "llm_llama_3_2_1b_instruct_q6_k",
|
| 186 |
+
"path": "llm/llama/llama-3.2-1b-q6_k.gguf",
|
| 187 |
"size": 1021800576,
|
| 188 |
"sha256": "0f4c510daf16e0d1b3bc94931fd9296c28936bebdda2593687d4eb70c5b70628",
|
| 189 |
"required": false
|
| 190 |
}
|
| 191 |
]
|
| 192 |
},
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 193 |
{
|
| 194 |
"id": "supertonic_tts",
|
| 195 |
"name": "Supertonic 3 TTS Engine",
|
|
|
|
| 255 |
"files": [
|
| 256 |
{
|
| 257 |
"id": "tts_chatterbox_t3",
|
| 258 |
+
"path": "tts/chatterbox/t3-q4_0.gguf",
|
| 259 |
"size": 344985408,
|
| 260 |
"sha256": "a7c8cbb267a836697a39757ada25a8ab095712b74961af2b86012dbd296a3a7b",
|
| 261 |
"required": false
|
| 262 |
},
|
| 263 |
{
|
| 264 |
"id": "tts_chatterbox_s3gen",
|
| 265 |
+
"path": "tts/chatterbox/s3gen-f16.gguf",
|
| 266 |
"size": 1056431360,
|
| 267 |
"sha256": "b25fe64c5b5287952c82684f6cadb12698257dfe8ed3d9e578801ca970b59664",
|
| 268 |
"required": false
|
|
|
|
| 279 |
},
|
| 280 |
{
|
| 281 |
"id": "bge_m3",
|
| 282 |
+
"name": "BGE-M3 Multilingual Embedding Engine (Fallback)",
|
| 283 |
"category": "embedding",
|
| 284 |
"version": "1.0.0",
|
| 285 |
"files": [
|
|
|
|
| 288 |
"path": "embedding/bge-m3/model_quantized.onnx",
|
| 289 |
"size": 569694530,
|
| 290 |
"sha256": "0826f8c1ab9edf1801db86c61919d4d108e8bfc0b809ec823ad366882ff0b77d",
|
| 291 |
+
"required": false
|
| 292 |
},
|
| 293 |
{
|
| 294 |
"id": "embedding_bge_m3_tokenizer",
|
| 295 |
"path": "embedding/bge-m3/tokenizer.json",
|
| 296 |
"size": 17082821,
|
| 297 |
"sha256": "6710678b12670bc442b99edc952c4d996ae309a7020c1fa0096dd245c2faf790",
|
| 298 |
+
"required": false
|
| 299 |
+
}
|
| 300 |
+
]
|
| 301 |
+
},
|
| 302 |
+
{
|
| 303 |
+
"id": "minilm_l12_v2",
|
| 304 |
+
"name": "MiniLM-L12 Multilingual Embedding Engine (Primary)",
|
| 305 |
+
"category": "embedding",
|
| 306 |
+
"version": "1.0.0",
|
| 307 |
+
"files": [
|
| 308 |
+
{
|
| 309 |
+
"id": "embedding_minilm_l12_onnx",
|
| 310 |
+
"path": "embedding/minilm-l12-v2/model_int8.onnx",
|
| 311 |
+
"size": 118054609,
|
| 312 |
+
"sha256": "4b76e8b4e72390a880356c38be28b9d363d6642d99dcf5c0c978bb7ecb3df637",
|
| 313 |
+
"required": true
|
| 314 |
+
},
|
| 315 |
+
{
|
| 316 |
+
"id": "embedding_minilm_l12_tokenizer",
|
| 317 |
+
"path": "embedding/minilm-l12-v2/tokenizer.json",
|
| 318 |
+
"size": 17082821,
|
| 319 |
+
"sha256": "6710678b12670bc442b99edc952c4d996ae309a7020c1fa0096dd245c2faf790",
|
| 320 |
"required": true
|
| 321 |
}
|
| 322 |
]
|
|
|
|
| 329 |
"files": [
|
| 330 |
{
|
| 331 |
"id": "nli_deberta_onnx",
|
| 332 |
+
"path": "nli/deberta-v3-xsmall/model_quantized.onnx",
|
| 333 |
"size": 87246587,
|
| 334 |
"sha256": "3fac2500c45c75af42c7711de0d1b93d59577456100208be0dc1f9e8811946b6",
|
| 335 |
"required": true
|
| 336 |
},
|
| 337 |
{
|
| 338 |
"id": "nli_deberta_tokenizer",
|
| 339 |
+
"path": "nli/deberta-v3-xsmall/tokenizer.json",
|
| 340 |
"size": 8656551,
|
| 341 |
"sha256": "a86f883318afa11c8c10466f1bf4efaeb6ded28a52cbe57217a8fa0d0a2a87df",
|
| 342 |
"required": true
|
nli/{deberta-v3-xsmall-nli → deberta-v3-xsmall}/model_quantized.onnx
RENAMED
|
File without changes
|
nli/{deberta-v3-xsmall-nli → deberta-v3-xsmall}/tokenizer.json
RENAMED
|
File without changes
|
stt/{nvidia-nemotron-3.5 → nemotron-3.5}/config.json
RENAMED
|
File without changes
|
stt/{nvidia-nemotron-3.5 → nemotron-3.5}/decoder_joint.onnx
RENAMED
|
File without changes
|
stt/{nvidia-nemotron-3.5 → nemotron-3.5}/encoder.onnx
RENAMED
|
File without changes
|
stt/{nvidia-nemotron-3.5 → nemotron-3.5}/tokenizer.model
RENAMED
|
File without changes
|
tts/chatterbox/{chatterbox-s3gen-mtl-f16.gguf → s3gen-f16.gguf}
RENAMED
|
File without changes
|
tts/chatterbox/{chatterbox-t3-mtl-q4_0.gguf → t3-q4_0.gguf}
RENAMED
|
File without changes
|