Instructions to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-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 chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0

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 chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0

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 chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF with Ollama:
```
ollama run hf.co/chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0
```

Unsloth Studio

How to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-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 chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-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 chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0
```

Lemonade

How to use chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF-Q8_0

List all available models

lemonade list

gemma-3-1b-it-thinking-32k-grpo-merged-Q8_0-GGUF / README.md

chimbiwide

Update README.md

7df7d52 verified 7 months ago

preview code

Raw

History Blame Contribute Delete

1.19 kB

metadata

license: apache-2.0
tags:
  - gemma
  - gemma3
  - tunix
  - grpo
  - reasoning
  - thinking
  - llama-cpp
  - gguf-my-repo
library_name: transformers
base_model: chimbiwide/gemma-3-1b-it-thinking-32k-grpo-merged

GemmaThink-32k-Q8_0-GGUF (GRPO Trained Model)

This model was trained using GRPO (Group Relative Policy Optimization) to generate structured reasoning traces.

Training Details

Base Model: google/gemma-3-1b-it
Training Method: SFT + GRPO
LoRA Rank: 32
LoRA Alpha: 64.0
Framework: Tunix (JAX)
Hardware: v6e-1 TPU in Colab

Output Format

<reasoning>step-by-step thinking process</reasoning>
<answer>final answer</answer>

Quicklinks:

SFT Base Model
SFT Base Model Q8 GGUF
GRPO Full Model
Q8-GGUF <-- You're here
Article