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fernandotonon
/
QtMeshEditor-models

ONNX
GGUF
pbr
texture
normal-map
qtmesheditor
qtmesh
qtmesh-cloud
conversational
Model card Files Files and versions
xet
Community

Instructions to use fernandotonon/QtMeshEditor-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • llama-cpp-python

    How to use fernandotonon/QtMeshEditor-models with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="fernandotonon/QtMeshEditor-models",
    	filename="caption/SmolVLM-500M-Instruct-Q8_0.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 fernandotonon/QtMeshEditor-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 fernandotonon/QtMeshEditor-models:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf fernandotonon/QtMeshEditor-models:Q8_0
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf fernandotonon/QtMeshEditor-models:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf fernandotonon/QtMeshEditor-models:Q8_0
    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 fernandotonon/QtMeshEditor-models:Q8_0
    # Run inference directly in the terminal:
    ./llama-cli -hf fernandotonon/QtMeshEditor-models:Q8_0
    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 fernandotonon/QtMeshEditor-models:Q8_0
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf fernandotonon/QtMeshEditor-models:Q8_0
    Use Docker
    docker model run hf.co/fernandotonon/QtMeshEditor-models:Q8_0
  • LM Studio
  • Jan
  • Ollama

    How to use fernandotonon/QtMeshEditor-models with Ollama:

    ollama run hf.co/fernandotonon/QtMeshEditor-models:Q8_0
  • Unsloth Studio

    How to use fernandotonon/QtMeshEditor-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 fernandotonon/QtMeshEditor-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 fernandotonon/QtMeshEditor-models to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for fernandotonon/QtMeshEditor-models to start chatting
  • Atomic Chat new
  • Docker Model Runner

    How to use fernandotonon/QtMeshEditor-models with Docker Model Runner:

    docker model run hf.co/fernandotonon/QtMeshEditor-models:Q8_0
  • Lemonade

    How to use fernandotonon/QtMeshEditor-models with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull fernandotonon/QtMeshEditor-models:Q8_0
    Run and chat with the model
    lemonade run user.QtMeshEditor-models-Q8_0
    List all available models
    lemonade list
QtMeshEditor-models / motion
21.9 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
fernandotonon's picture
fernandotonon
t2m: retrain with corrected 6D rotation packing (#411, PR #792 review)
c9548ee verified 6 days ago
  • motion-library.json
    4.19 MB
    motion library v4: 47 active-window clips / 15 actions with per-action variety (#411) 6 days ago
  • t2m-vocab.json
    412 Bytes
    t2m v4 vocab: 13 actions, frame=world, fps=30 (#411) 6 days ago
  • t2m.onnx
    17.7 MB
    xet
    t2m: retrain with corrected 6D rotation packing (#411, PR #792 review) 6 days ago