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

Libraries

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

fernandotonon commited on 16 days ago

Commit

5ac8f75

verified ·

1 Parent(s): de5db01

Update README.md

Browse files

Files changed (1) hide show

README.md +8 -6

README.md CHANGED Viewed

@@ -1,11 +1,13 @@
 ---
 license: cc0-1.0
 tags:
-  - onnx
-  - pbr
-  - texture
-  - normal-map
-  - qtmesheditor
 library_name: onnx
 ---
@@ -32,4 +34,4 @@ CC0-1.0), trained on CC0 content from ambientCG / Poly Haven. Converted with
 QtMeshEditor downloads these on first use into `<AppData>/ai_models/pbr/`.
-More info in [QtMesh Cloud website](https://qtmesh.dev)

 ---
 license: cc0-1.0
 tags:
+- onnx
+- pbr
+- texture
+- normal-map
+- qtmesheditor
+- qtmesh
+- qtmesh-cloud
 library_name: onnx
 ---
 QtMeshEditor downloads these on first use into `<AppData>/ai_models/pbr/`.
+More info in [QtMesh Cloud website](https://qtmesh.dev)