Instructions to use FINAL-Bench/POCKET-26B-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 FINAL-Bench/POCKET-26B-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 FINAL-Bench/POCKET-26B-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K

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 FINAL-Bench/POCKET-26B-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K

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 FINAL-Bench/POCKET-26B-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K

Use Docker

docker model run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K

LM Studio
Jan

vLLM

How to use FINAL-Bench/POCKET-26B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FINAL-Bench/POCKET-26B-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": "FINAL-Bench/POCKET-26B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K

Ollama
How to use FINAL-Bench/POCKET-26B-GGUF with Ollama:
```
ollama run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K
```
Unsloth Desktop
Docker Model Runner
How to use FINAL-Bench/POCKET-26B-GGUF with Docker Model Runner:
```
docker model run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K
```

Lemonade

How to use FINAL-Bench/POCKET-26B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull FINAL-Bench/POCKET-26B-GGUF:Q2_K

Run and chat with the model

lemonade run user.POCKET-26B-GGUF-Q2_K

List all available models

lemonade list

Atomic Chat

Template fix =good performance

by Andropano - opened Aug 18

Discussion

Andropano

Aug 18

I just want to Say here that once you use the last template of google with this model, not the one in the gguf, it performs very well, I'm kinda impressed by the preservation of Gemma 4 26B. I hope you will make qwen 3.8 35B A3B once it will be released. Anyway, thank you for this model.

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