Text Generation
PEFT
GGUF
gemma4
llama.cpp
unsloth
vision-language-model
rp
roleplay
story
ai-gf
character
bitsandbytes
conversational
Instructions to use samunder12/Gemma4-2b-DietCoke with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use samunder12/Gemma4-2b-DietCoke with PEFT:
Task type is invalid.
- llama-cpp-python
How to use samunder12/Gemma4-2b-DietCoke with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="samunder12/Gemma4-2b-DietCoke", filename="gemma-4-e2b-DietCoke.F16-mmproj.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use samunder12/Gemma4-2b-DietCoke 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 samunder12/Gemma4-2b-DietCoke:F16 # Run inference directly in the terminal: llama cli -hf samunder12/Gemma4-2b-DietCoke:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf samunder12/Gemma4-2b-DietCoke:F16 # Run inference directly in the terminal: llama cli -hf samunder12/Gemma4-2b-DietCoke:F16
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 samunder12/Gemma4-2b-DietCoke:F16 # Run inference directly in the terminal: ./llama-cli -hf samunder12/Gemma4-2b-DietCoke:F16
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 samunder12/Gemma4-2b-DietCoke:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf samunder12/Gemma4-2b-DietCoke:F16
Use Docker
docker model run hf.co/samunder12/Gemma4-2b-DietCoke:F16
- LM Studio
- Jan
- vLLM
How to use samunder12/Gemma4-2b-DietCoke with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "samunder12/Gemma4-2b-DietCoke" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "samunder12/Gemma4-2b-DietCoke", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/samunder12/Gemma4-2b-DietCoke:F16
- Ollama
How to use samunder12/Gemma4-2b-DietCoke with Ollama:
ollama run hf.co/samunder12/Gemma4-2b-DietCoke:F16
- Unsloth Studio
How to use samunder12/Gemma4-2b-DietCoke 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 samunder12/Gemma4-2b-DietCoke 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 samunder12/Gemma4-2b-DietCoke to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for samunder12/Gemma4-2b-DietCoke to start chatting
- Atomic Chat new
- Docker Model Runner
How to use samunder12/Gemma4-2b-DietCoke with Docker Model Runner:
docker model run hf.co/samunder12/Gemma4-2b-DietCoke:F16
- Lemonade
How to use samunder12/Gemma4-2b-DietCoke with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull samunder12/Gemma4-2b-DietCoke:F16
Run and chat with the model
lemonade run user.Gemma4-2b-DietCoke-F16
List all available models
lemonade list
Gemma-2b-DietCoke : GGUF
This model was finetuned and converted to GGUF format using Unsloth.
Example usage:
- For text only LLMs:
llama-cli -hf samunder12/Gemma-2b-DietCoke --jinja - For multimodal models:
llama-mtmd-cli -hf samunder12/Gemma-2b-DietCoke --jinja
Available Model files:
gemma-4-e2b-it.Q4_K_M.ggufgemma-4-e2b-it.F16-mmproj.gguf
⚠️ Ollama Note for Vision Models
Important: Ollama currently does not support separate mmproj files for vision models.
To create an Ollama model from this vision model:
- Place the
Modelfilein the same directory as the finetuned bf16 merged model - Run:
ollama create model_name -f ./Modelfile(Replacemodel_namewith your desired name)
This will create a unified bf16 model that Ollama can use.
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Hardware compatibility
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4-bit