Instructions to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DestinyApocalypse/apocalypse-aid-gemma4-e2b") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("DestinyApocalypse/apocalypse-aid-gemma4-e2b") model = AutoModelForImageTextToText.from_pretrained("DestinyApocalypse/apocalypse-aid-gemma4-e2b") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - MLX
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("DestinyApocalypse/apocalypse-aid-gemma4-e2b") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - llama-cpp-python
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="DestinyApocalypse/apocalypse-aid-gemma4-e2b", filename="gemma-4-E2B-survival-v2-f16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16 # Run inference directly in the terminal: llama-cli -hf DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16 # Run inference directly in the terminal: llama-cli -hf DestinyApocalypse/apocalypse-aid-gemma4-e2b: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 DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16 # Run inference directly in the terminal: ./llama-cli -hf DestinyApocalypse/apocalypse-aid-gemma4-e2b: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 DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
Use Docker
docker model run hf.co/DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
- LM Studio
- Jan
- vLLM
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DestinyApocalypse/apocalypse-aid-gemma4-e2b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DestinyApocalypse/apocalypse-aid-gemma4-e2b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
- SGLang
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "DestinyApocalypse/apocalypse-aid-gemma4-e2b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DestinyApocalypse/apocalypse-aid-gemma4-e2b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "DestinyApocalypse/apocalypse-aid-gemma4-e2b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DestinyApocalypse/apocalypse-aid-gemma4-e2b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with Ollama:
ollama run hf.co/DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
- Unsloth Studio
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b 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 DestinyApocalypse/apocalypse-aid-gemma4-e2b 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 DestinyApocalypse/apocalypse-aid-gemma4-e2b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DestinyApocalypse/apocalypse-aid-gemma4-e2b to start chatting
- Pi
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "DestinyApocalypse/apocalypse-aid-gemma4-e2b"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "DestinyApocalypse/apocalypse-aid-gemma4-e2b" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "DestinyApocalypse/apocalypse-aid-gemma4-e2b"
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 DestinyApocalypse/apocalypse-aid-gemma4-e2b
Run Hermes
hermes
- MLX LM
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "DestinyApocalypse/apocalypse-aid-gemma4-e2b"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "DestinyApocalypse/apocalypse-aid-gemma4-e2b" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DestinyApocalypse/apocalypse-aid-gemma4-e2b", "messages": [ {"role": "user", "content": "Hello"} ] }' - Docker Model Runner
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with Docker Model Runner:
docker model run hf.co/DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
- Lemonade
How to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DestinyApocalypse/apocalypse-aid-gemma4-e2b:F16
Run and chat with the model
lemonade run user.apocalypse-aid-gemma4-e2b-F16
List all available models
lemonade list