Instructions to use DestinyApocalypse/apocalypse-aid-gemma4-e2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

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

apocalypse-aid-gemma4-e2b / generation_config.json

DestinyApocalypse

Upload merged HF weights (fused v2 adapter)

b7608d5 verified 21 days ago

raw

history blame contribute delete

208 Bytes

	{
	"bos_token_id": 2,
	"do_sample": true,
	"eos_token_id": [
	1,
	106,
	50
	],
	"pad_token_id": 0,
	"temperature": 1.0,
	"top_k": 64,
	"top_p": 0.95,
	"transformers_version": "5.5.0.dev0"
	}