Instructions to use Myric/granite-4.0-h-tiny-APEX-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 Myric/granite-4.0-h-tiny-APEX-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 Myric/granite-4.0-h-tiny-APEX-GGUF
# Run inference directly in the terminal:
llama cli -hf Myric/granite-4.0-h-tiny-APEX-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Myric/granite-4.0-h-tiny-APEX-GGUF
# Run inference directly in the terminal:
llama cli -hf Myric/granite-4.0-h-tiny-APEX-GGUF

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 Myric/granite-4.0-h-tiny-APEX-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Myric/granite-4.0-h-tiny-APEX-GGUF

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 Myric/granite-4.0-h-tiny-APEX-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Myric/granite-4.0-h-tiny-APEX-GGUF

Use Docker

docker model run hf.co/Myric/granite-4.0-h-tiny-APEX-GGUF

LM Studio
Jan

vLLM

How to use Myric/granite-4.0-h-tiny-APEX-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Myric/granite-4.0-h-tiny-APEX-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": "Myric/granite-4.0-h-tiny-APEX-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Myric/granite-4.0-h-tiny-APEX-GGUF

Ollama
How to use Myric/granite-4.0-h-tiny-APEX-GGUF with Ollama:
```
ollama run hf.co/Myric/granite-4.0-h-tiny-APEX-GGUF
```
Unsloth Desktop

How to use Myric/granite-4.0-h-tiny-APEX-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Myric/granite-4.0-h-tiny-APEX-GGUF

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Myric/granite-4.0-h-tiny-APEX-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Myric/granite-4.0-h-tiny-APEX-GGUF with Docker Model Runner:
```
docker model run hf.co/Myric/granite-4.0-h-tiny-APEX-GGUF
```

Lemonade

How to use Myric/granite-4.0-h-tiny-APEX-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Myric/granite-4.0-h-tiny-APEX-GGUF

Run and chat with the model

lemonade run user.granite-4.0-h-tiny-APEX-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use Myric/granite-4.0-h-tiny-APEX-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 Myric/granite-4.0-h-tiny-APEX-GGUF

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 Myric/granite-4.0-h-tiny-APEX-GGUF

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Myric/granite-4.0-h-tiny-APEX-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Myric/granite-4.0-h-tiny-APEX-GGUF

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 "Myric/granite-4.0-h-tiny-APEX-GGUF" \
  --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"

Myric commited on Jul 20

Commit

3fbd96f

verified ·

1 Parent(s): 3e77dba

Upload configs/granite_i-quality.txt with huggingface_hub

Browse files

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configs/granite_i-quality.txt +520 -0

configs/granite_i-quality.txt ADDED Viewed

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+blk.26.ssm_in=Q6_K
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+blk.27.ffn_gate_exps=iq4_xs
+blk.27.ffn_up_exps=iq4_xs
+blk.27.ffn_down_exps=iq4_xs
+blk.27.ffn_gate_shexp=Q8_0
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+blk.27.ffn_down_shexp=Q8_0
+blk.27.attn_q=Q6_K
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+blk.27.attn_v=Q6_K
+blk.27.attn_output=Q6_K
+blk.27.ssm_in=Q6_K
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+blk.27.ssm_out=Q6_K
+blk.28.ffn_gate_exps=iq4_xs
+blk.28.ffn_up_exps=iq4_xs
+blk.28.ffn_down_exps=iq4_xs
+blk.28.ffn_gate_shexp=Q8_0
+blk.28.ffn_up_shexp=Q8_0
+blk.28.ffn_down_shexp=Q8_0
+blk.28.attn_q=Q6_K
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+blk.28.attn_v=Q6_K
+blk.28.attn_output=Q6_K
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+blk.28.ssm_conv1d=Q6_K
+blk.28.ssm_out=Q6_K
+blk.29.ffn_gate_exps=iq4_xs
+blk.29.ffn_up_exps=iq4_xs
+blk.29.ffn_down_exps=iq4_xs
+blk.29.ffn_gate_shexp=Q8_0
+blk.29.ffn_up_shexp=Q8_0
+blk.29.ffn_down_shexp=Q8_0
+blk.29.attn_q=Q6_K
+blk.29.attn_k=Q6_K
+blk.29.attn_v=Q6_K
+blk.29.attn_output=Q6_K
+blk.29.ssm_in=Q6_K
+blk.29.ssm_conv1d=Q6_K
+blk.29.ssm_out=Q6_K
+blk.30.ffn_gate_exps=Q5_K
+blk.30.ffn_up_exps=Q5_K
+blk.30.ffn_down_exps=Q5_K
+blk.30.ffn_gate_shexp=Q8_0
+blk.30.ffn_up_shexp=Q8_0
+blk.30.ffn_down_shexp=Q8_0
+blk.30.attn_q=Q6_K
+blk.30.attn_k=Q6_K
+blk.30.attn_v=Q6_K
+blk.30.attn_output=Q6_K
+blk.30.ssm_in=Q6_K
+blk.30.ssm_conv1d=Q6_K
+blk.30.ssm_out=Q6_K
+blk.31.ffn_gate_exps=Q5_K
+blk.31.ffn_up_exps=Q5_K
+blk.31.ffn_down_exps=Q5_K
+blk.31.ffn_gate_shexp=Q8_0
+blk.31.ffn_up_shexp=Q8_0
+blk.31.ffn_down_shexp=Q8_0
+blk.31.attn_q=Q6_K
+blk.31.attn_k=Q6_K
+blk.31.attn_v=Q6_K
+blk.31.attn_output=Q6_K
+blk.31.ssm_in=Q6_K
+blk.31.ssm_conv1d=Q6_K
+blk.31.ssm_out=Q6_K
+blk.32.ffn_gate_exps=Q5_K
+blk.32.ffn_up_exps=Q5_K
+blk.32.ffn_down_exps=Q5_K
+blk.32.ffn_gate_shexp=Q8_0
+blk.32.ffn_up_shexp=Q8_0
+blk.32.ffn_down_shexp=Q8_0
+blk.32.attn_q=Q6_K
+blk.32.attn_k=Q6_K
+blk.32.attn_v=Q6_K
+blk.32.attn_output=Q6_K
+blk.32.ssm_in=Q6_K
+blk.32.ssm_conv1d=Q6_K
+blk.32.ssm_out=Q6_K
+blk.33.ffn_gate_exps=Q5_K
+blk.33.ffn_up_exps=Q5_K
+blk.33.ffn_down_exps=Q5_K
+blk.33.ffn_gate_shexp=Q8_0
+blk.33.ffn_up_shexp=Q8_0
+blk.33.ffn_down_shexp=Q8_0
+blk.33.attn_q=Q6_K
+blk.33.attn_k=Q6_K
+blk.33.attn_v=Q6_K
+blk.33.attn_output=Q6_K
+blk.33.ssm_in=Q6_K
+blk.33.ssm_conv1d=Q6_K
+blk.33.ssm_out=Q6_K
+blk.34.ffn_gate_exps=Q5_K
+blk.34.ffn_up_exps=Q5_K
+blk.34.ffn_down_exps=Q5_K
+blk.34.ffn_gate_shexp=Q8_0
+blk.34.ffn_up_shexp=Q8_0
+blk.34.ffn_down_shexp=Q8_0
+blk.34.attn_q=Q6_K
+blk.34.attn_k=Q6_K
+blk.34.attn_v=Q6_K
+blk.34.attn_output=Q6_K
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+blk.34.ssm_conv1d=Q6_K
+blk.34.ssm_out=Q6_K
+blk.35.ffn_gate_exps=Q6_K
+blk.35.ffn_up_exps=Q6_K
+blk.35.ffn_down_exps=Q6_K
+blk.35.ffn_gate_shexp=Q8_0
+blk.35.ffn_up_shexp=Q8_0
+blk.35.ffn_down_shexp=Q8_0
+blk.35.attn_q=Q6_K
+blk.35.attn_k=Q6_K
+blk.35.attn_v=Q6_K
+blk.35.attn_output=Q6_K
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+blk.35.ssm_conv1d=Q6_K
+blk.35.ssm_out=Q6_K
+blk.36.ffn_gate_exps=Q6_K
+blk.36.ffn_up_exps=Q6_K
+blk.36.ffn_down_exps=Q6_K
+blk.36.ffn_gate_shexp=Q8_0
+blk.36.ffn_up_shexp=Q8_0
+blk.36.ffn_down_shexp=Q8_0
+blk.36.attn_q=Q6_K
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+blk.36.attn_v=Q6_K
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+blk.37.ffn_gate_exps=Q6_K
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+blk.37.ffn_down_exps=Q6_K
+blk.37.ffn_gate_shexp=Q8_0
+blk.37.ffn_up_shexp=Q8_0
+blk.37.ffn_down_shexp=Q8_0
+blk.37.attn_q=Q6_K
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+blk.37.attn_output=Q6_K
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+blk.38.ffn_gate_exps=Q6_K
+blk.38.ffn_up_exps=Q6_K
+blk.38.ffn_down_exps=Q6_K
+blk.38.ffn_gate_shexp=Q8_0
+blk.38.ffn_up_shexp=Q8_0
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+blk.38.attn_q=Q6_K
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+blk.38.attn_output=Q6_K
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+blk.39.ffn_gate_exps=Q6_K
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+blk.39.ffn_down_exps=Q6_K
+blk.39.ffn_gate_shexp=Q8_0
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+blk.39.attn_q=Q6_K
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