Instructions to use Zhantas/DeepGemma-2B-Reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zhantas/DeepGemma-2B-Reasoning with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Zhantas/DeepGemma-2B-Reasoning", dtype="auto") - llama-cpp-python
How to use Zhantas/DeepGemma-2B-Reasoning with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Zhantas/DeepGemma-2B-Reasoning", filename="gemma4_e2b-q4_k_m.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Zhantas/DeepGemma-2B-Reasoning with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
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 Zhantas/DeepGemma-2B-Reasoning:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
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 Zhantas/DeepGemma-2B-Reasoning:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
Use Docker
docker model run hf.co/Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Zhantas/DeepGemma-2B-Reasoning with Ollama:
ollama run hf.co/Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
- Unsloth Studio new
How to use Zhantas/DeepGemma-2B-Reasoning 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 Zhantas/DeepGemma-2B-Reasoning 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 Zhantas/DeepGemma-2B-Reasoning to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Zhantas/DeepGemma-2B-Reasoning to start chatting
- Pi new
How to use Zhantas/DeepGemma-2B-Reasoning with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
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": "Zhantas/DeepGemma-2B-Reasoning:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Zhantas/DeepGemma-2B-Reasoning with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
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 Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use Zhantas/DeepGemma-2B-Reasoning with Docker Model Runner:
docker model run hf.co/Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
- Lemonade
How to use Zhantas/DeepGemma-2B-Reasoning with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Zhantas/DeepGemma-2B-Reasoning:Q4_K_M
Run and chat with the model
lemonade run user.DeepGemma-2B-Reasoning-Q4_K_M
List all available models
lemonade list
why claude?
I mean your training on 1.000.000 kimi q-a and 5B kimi tokens… the claude data is less than 20k. It does not really make a difference, unless you first train on kimi and afterwards on claude
I didn't use the full 1M Kimi dataset. I only took a 30,000 sample from it for this run. Combined with 16,000 Claude examples, the dataset is well-balanced (35% Claude), so joint training works fine without dilution...
bro i was using this model for my sexual intercorse roleplay and during the ejaculation phase it decided that it wanted to go all safety mode on me, fix ur dogshi model pls and thank u sir