Instructions to use chimbiwide/GemmaReLe-Q4-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chimbiwide/GemmaReLe-Q4-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chimbiwide/GemmaReLe-Q4-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use chimbiwide/GemmaReLe-Q4-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/GemmaReLe-Q4-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
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/GemmaReLe-Q4-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
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/GemmaReLe-Q4-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
Use Docker
docker model run hf.co/chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use chimbiwide/GemmaReLe-Q4-GGUF with Ollama:
ollama run hf.co/chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use chimbiwide/GemmaReLe-Q4-GGUF with Docker Model Runner:
docker model run hf.co/chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
- Lemonade
How to use chimbiwide/GemmaReLe-Q4-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull chimbiwide/GemmaReLe-Q4-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.GemmaReLe-Q4-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
GemmaReLe
A test model for ReLe
(btw, we sort of did)
The Q4_K_M version of GemmaReLe-float16.
The Gemma3NPC series were meant to be a sort of general purposed video game RP model.
This time, using the chimbiwide/ReLe_Synthetic_v1_json, we trained a model to specifically act as ReLe.
For more information on Who is ReLe?, visit the dataset README.
Warning: This is NOT a general purpose model. Performance requires further testing.
Check out our training notebook here
Training parameters compared to Gemma3NPC-it
| Parameter | Gemma3NPC-it | Gemma3NPC-it-beta |
|---|---|---|
| Learning Rate | 2e-5 | 2.5e-5 (+25%) |
| Warmup Steps | 800 | 100 |
| gradient clipping | 0.4 | 1.0 |
Graph of the Step Training Loss, saved every 10 steps:
Fun Discovery
For the first time ever, we encountered a whole number trianing loss.
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Base model
chimbiwide/GemmaReLe

