Instructions to use Aname-Tommy/Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Aname-Tommy/Test with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Aname-Tommy/Test", filename="Qwen3.5-FT-Japanese-CoT-4B.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Aname-Tommy/Test 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 Aname-Tommy/Test # Run inference directly in the terminal: llama cli -hf Aname-Tommy/Test
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Aname-Tommy/Test # Run inference directly in the terminal: llama cli -hf Aname-Tommy/Test
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 Aname-Tommy/Test # Run inference directly in the terminal: ./llama-cli -hf Aname-Tommy/Test
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 Aname-Tommy/Test # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aname-Tommy/Test
Use Docker
docker model run hf.co/Aname-Tommy/Test
- LM Studio
- Jan
- Ollama
How to use Aname-Tommy/Test with Ollama:
ollama run hf.co/Aname-Tommy/Test
- Unsloth Studio
How to use Aname-Tommy/Test 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 Aname-Tommy/Test 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 Aname-Tommy/Test to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aname-Tommy/Test to start chatting
- Pi
How to use Aname-Tommy/Test with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Aname-Tommy/Test
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": "Aname-Tommy/Test" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Aname-Tommy/Test with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Aname-Tommy/Test
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 Aname-Tommy/Test
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Aname-Tommy/Test with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Aname-Tommy/Test
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 "Aname-Tommy/Test" \ --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"
- Docker Model Runner
How to use Aname-Tommy/Test with Docker Model Runner:
docker model run hf.co/Aname-Tommy/Test
- Lemonade
How to use Aname-Tommy/Test with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aname-Tommy/Test
Run and chat with the model
lemonade run user.Test-{{QUANT_TAG}}List all available models
lemonade list
What is this model?
I tried using it, and it seems to separate the inst (instrumental) into the low frequencies and vocals into the high frequencies. What would be some good use cases for this?
this model is for next release, I change to public this repo to upload, so Dont mind to this repo
For next releases, I would like to use your Mel Roformer cinematic speech separation, for separate two speakers or more.
btw, I tried to use test3.ckpt but it gives me an error on torch size.
Please, fix this model error, I tried to use your model and nothing, it gives me always the same error on torch size and everything! Or what model type is your new test model?
Have you got any updated config for your new model?
Gobzaluigi, I will upload new model soon about a day, And I must say this model is so big. config will be publicly soon, so please wait a bit.
Ok, thanks for your information.
Gobzaluigi, What is Mel Roformer cinematic speech separation? If I could understand that, I may be able to make for that model.
Gobzaluigi, What is Mel Roformer cinematic speech separation? If I could understand that, I may be able to make for that model.
I'll explain you. Mel Roformer cinematic speech separation will be a Mel Band Roformer model that isolates main speech from multiple speeches, and it's the speech separation model with multilingual speech (including spanish, both castillian and latin american)