Instructions to use ddtsoftware/gemma3-jarvic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ddtsoftware/gemma3-jarvic with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ddtsoftware/gemma3-jarvic",
	filename="gemma3-custom.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 ddtsoftware/gemma3-jarvic with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ddtsoftware/gemma3-jarvic
# Run inference directly in the terminal:
llama-cli -hf ddtsoftware/gemma3-jarvic

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ddtsoftware/gemma3-jarvic
# Run inference directly in the terminal:
llama-cli -hf ddtsoftware/gemma3-jarvic

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 ddtsoftware/gemma3-jarvic
# Run inference directly in the terminal:
./llama-cli -hf ddtsoftware/gemma3-jarvic

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 ddtsoftware/gemma3-jarvic
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ddtsoftware/gemma3-jarvic

Use Docker

docker model run hf.co/ddtsoftware/gemma3-jarvic

LM Studio
Jan
Ollama
How to use ddtsoftware/gemma3-jarvic with Ollama:
```
ollama run hf.co/ddtsoftware/gemma3-jarvic
```

Unsloth Studio

How to use ddtsoftware/gemma3-jarvic 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 ddtsoftware/gemma3-jarvic 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 ddtsoftware/gemma3-jarvic to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ddtsoftware/gemma3-jarvic to start chatting

Docker Model Runner
How to use ddtsoftware/gemma3-jarvic with Docker Model Runner:
```
docker model run hf.co/ddtsoftware/gemma3-jarvic
```

Lemonade

How to use ddtsoftware/gemma3-jarvic with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ddtsoftware/gemma3-jarvic

Run and chat with the model

lemonade run user.gemma3-jarvic-{{QUANT_TAG}}

List all available models

lemonade list

ddtsoftware commited on Dec 29, 2025

Commit

64c54de

verified ·

1 Parent(s): 8e7a286

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@@ -1,25 +0,0 @@
-FROM ./gemma3-custom.gguf
-TEMPLATE """
-{{- if .System }}<start_of_turn>system
-{{ .System }}<end_of_turn>
-{{- end }}
-{{- range .Messages }}
-<start_of_turn>{{ .Role }}
-{{ .Content }}<end_of_turn>
-{{- end }}
-<start_of_turn>model
-"""
-SYSTEM """
-คุณคือผู้ช่วย AI ภาษาไทย
-ตอบเป็นภาษาไทยเป็นหลัก
-ตอบให้สุภาพ ชัดเจน และเป็นธรรมชาติ
-"""
-PARAMETER temperature 0.7
-PARAMETER top_p 0.9
-PARAMETER top_k 40
-PARAMETER repeat_penalty 1.1
-PARAMETER num_ctx 2048
-PARAMETER stop "<end_of_turn>"