Instructions to use AtomicChat/gemma-4-E4B-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use AtomicChat/gemma-4-E4B-it-GGUF 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 AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama cli -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama cli -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

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 AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./llama-cli -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

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 AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

Use Docker

docker model run hf.co/AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

LM Studio
Jan

vLLM

How to use AtomicChat/gemma-4-E4B-it-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AtomicChat/gemma-4-E4B-it-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AtomicChat/gemma-4-E4B-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

Ollama
How to use AtomicChat/gemma-4-E4B-it-GGUF with Ollama:
```
ollama run hf.co/AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL
```

Unsloth Studio

How to use AtomicChat/gemma-4-E4B-it-GGUF 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 AtomicChat/gemma-4-E4B-it-GGUF 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 AtomicChat/gemma-4-E4B-it-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AtomicChat/gemma-4-E4B-it-GGUF to start chatting

How to use AtomicChat/gemma-4-E4B-it-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

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": "AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use AtomicChat/gemma-4-E4B-it-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use AtomicChat/gemma-4-E4B-it-GGUF with Docker Model Runner:
```
docker model run hf.co/AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL
```

Lemonade

How to use AtomicChat/gemma-4-E4B-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

Run and chat with the model

lemonade run user.gemma-4-E4B-it-GGUF-UD-Q4_K_XL

List all available models

lemonade list

Hermes Agent

How to use AtomicChat/gemma-4-E4B-it-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

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 AtomicChat/gemma-4-E4B-it-GGUF:UD-Q4_K_XL

Run Hermes

hermes

Atomic Chat

AlexAtomic commited on Jun 17

Commit

2643d97

verified ·

1 Parent(s): 9441404

point internal refs to AtomicChat org

Browse files

Files changed (1) hide show

README.md +11 -11

README.md CHANGED Viewed

@@ -1,11 +1,11 @@
 ---
 license: apache-2.0
 license_link: https://ai.google.dev/gemma/docs/gemma_4_license
-thumbnail: https://huggingface.co/AlexAtomic/gemma4-e4b-it-GGUF/resolve/main/hero.png
 base_model:
 - google/gemma-4-E4B-it
 base_model_relation: quantized
-quantized_by: AlexAtomic
 pipeline_tag: image-text-to-text
 library_name: gguf
 tags:
@@ -22,14 +22,14 @@ tags:
 <center>
 <div style="display:flex; justify-content:center; align-items:center; gap:10px; flex-wrap:wrap;">
-<a href="https://atomic.chat"><img src="https://huggingface.co/AlexAtomic/gemma4-e4b-it-GGUF/resolve/main/pill_atomic_v3.png" alt="Atomic Chat" width="186"></a>
-<a href="https://discord.gg/8wGSsvmg4V"><img src="https://huggingface.co/AlexAtomic/gemma4-e4b-it-GGUF/resolve/main/pill_discord_v3.png" alt="Join Discord" width="184"></a>
-<a href="https://github.com/AtomicBot-ai/Atomic-Chat"><img src="https://huggingface.co/AlexAtomic/gemma4-e4b-it-GGUF/resolve/main/pill_github_v3.png" alt="GitHub" width="141"></a>
 </div>
 <br/>
-<img src="https://huggingface.co/AlexAtomic/gemma4-e4b-it-GGUF/resolve/main/hero.png" alt="Gemma 4 E4B" style="width:100%; max-width:100%; height:auto; margin-bottom:0.6em;"/>
 <div style="display:flex; justify-content:center; gap:0.5em;">
 <a href="https://huggingface.co/google/gemma-4-E4B-it"><strong>Base model: google/gemma-4-E4B-it</strong></a>
@@ -69,7 +69,7 @@ tags:
 > [!NOTE]
 > Gemma 4 E4B is multimodal. This repo ships the **`mmproj-gemma4-e4b-it-f16.gguf`** vision projector. With `-hf` it is pulled automatically; otherwise pass `--mmproj`. Use `llama-mtmd-cli` or `llama-server` to feed images.
-<img src="https://huggingface.co/AlexAtomic/gemma4-e4b-it-GGUF/resolve/main/benchmark.png" alt="Gemma 4 E4B benchmark scores" style="width:100%; max-width:900px;"/>
 Scores are Google's published results for the base `google/gemma-4-E4B-it`. Quantization preserves the large majority of this; `Q4_K_M` and up sit within a point or two of full precision.
@@ -97,9 +97,9 @@ Scores are Google's published results for the base `google/gemma-4-E4B-it`. Quan
 Run Gemma 4 E4B locally with:
-- **[Atomic Chat](https://atomic.chat):** the easiest path. Open the app, search `AlexAtomic/gemma4-e4b-it-GGUF`, pick a quant, hit **Use this model**.
-- **llama.cpp:** `llama-server -hf AlexAtomic/gemma4-e4b-it-GGUF:Q4_K_M --jinja -c 8192`
-- **Ollama:** `ollama run hf.co/AlexAtomic/gemma4-e4b-it-GGUF:Q4_K_M`
 - **LM Studio / Jan:** search the repo id, download any quant.
 ## Best practices
@@ -122,7 +122,7 @@ cmake --build llama.cpp/build --config Release -j --target llama-cli llama-serve
 ```bash
 ./llama.cpp/build/bin/llama-server \
-    -hf AlexAtomic/gemma4-e4b-it-GGUF:UD-Q4_K_XL \
     --jinja -ngl 99 -c 8192 -fa on
 ```

 ---
 license: apache-2.0
 license_link: https://ai.google.dev/gemma/docs/gemma_4_license
+thumbnail: https://huggingface.co/AtomicChat/gemma4-e4b-it-GGUF/resolve/main/hero.png
 base_model:
 - google/gemma-4-E4B-it
 base_model_relation: quantized
+quantized_by: AtomicChat
 pipeline_tag: image-text-to-text
 library_name: gguf
 tags:
 <center>
 <div style="display:flex; justify-content:center; align-items:center; gap:10px; flex-wrap:wrap;">
+<a href="https://atomic.chat"><img src="https://huggingface.co/AtomicChat/gemma4-e4b-it-GGUF/resolve/main/pill_atomic_v3.png" alt="Atomic Chat" width="186"></a>
+<a href="https://discord.gg/8wGSsvmg4V"><img src="https://huggingface.co/AtomicChat/gemma4-e4b-it-GGUF/resolve/main/pill_discord_v3.png" alt="Join Discord" width="184"></a>
+<a href="https://github.com/AtomicBot-ai/Atomic-Chat"><img src="https://huggingface.co/AtomicChat/gemma4-e4b-it-GGUF/resolve/main/pill_github_v3.png" alt="GitHub" width="141"></a>
 </div>
 <br/>
+<img src="https://huggingface.co/AtomicChat/gemma4-e4b-it-GGUF/resolve/main/hero.png" alt="Gemma 4 E4B" style="width:100%; max-width:100%; height:auto; margin-bottom:0.6em;"/>
 <div style="display:flex; justify-content:center; gap:0.5em;">
 <a href="https://huggingface.co/google/gemma-4-E4B-it"><strong>Base model: google/gemma-4-E4B-it</strong></a>
 > [!NOTE]
 > Gemma 4 E4B is multimodal. This repo ships the **`mmproj-gemma4-e4b-it-f16.gguf`** vision projector. With `-hf` it is pulled automatically; otherwise pass `--mmproj`. Use `llama-mtmd-cli` or `llama-server` to feed images.
+<img src="https://huggingface.co/AtomicChat/gemma4-e4b-it-GGUF/resolve/main/benchmark.png" alt="Gemma 4 E4B benchmark scores" style="width:100%; max-width:900px;"/>
 Scores are Google's published results for the base `google/gemma-4-E4B-it`. Quantization preserves the large majority of this; `Q4_K_M` and up sit within a point or two of full precision.
 Run Gemma 4 E4B locally with:
+- **[Atomic Chat](https://atomic.chat):** the easiest path. Open the app, search `AtomicChat/gemma4-e4b-it-GGUF`, pick a quant, hit **Use this model**.
+- **llama.cpp:** `llama-server -hf AtomicChat/gemma4-e4b-it-GGUF:Q4_K_M --jinja -c 8192`
+- **Ollama:** `ollama run hf.co/AtomicChat/gemma4-e4b-it-GGUF:Q4_K_M`
 - **LM Studio / Jan:** search the repo id, download any quant.
 ## Best practices
 ```bash
 ./llama.cpp/build/bin/llama-server \
+    -hf AtomicChat/gemma4-e4b-it-GGUF:UD-Q4_K_XL \
     --jinja -ngl 99 -c 8192 -fa on
 ```