Instructions to use ataeff/g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ataeff/g with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-270m-it")
model = PeftModel.from_pretrained(base_model, "ataeff/g")

llama-cpp-python

How to use ataeff/g with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ataeff/g",
	filename="leo-1b-plain-q4.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use ataeff/g with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ataeff/g:F16
# Run inference directly in the terminal:
llama-cli -hf ataeff/g:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ataeff/g:F16
# Run inference directly in the terminal:
llama-cli -hf ataeff/g:F16

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 ataeff/g:F16
# Run inference directly in the terminal:
./llama-cli -hf ataeff/g:F16

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 ataeff/g:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ataeff/g:F16

Use Docker

docker model run hf.co/ataeff/g:F16

LM Studio
Jan

vLLM

How to use ataeff/g with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ataeff/g"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ataeff/g",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ataeff/g:F16

Ollama
How to use ataeff/g with Ollama:
```
ollama run hf.co/ataeff/g:F16
```

Unsloth Studio new

How to use ataeff/g 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 ataeff/g 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 ataeff/g to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ataeff/g to start chatting

Docker Model Runner
How to use ataeff/g with Docker Model Runner:
```
docker model run hf.co/ataeff/g:F16
```

Lemonade

How to use ataeff/g with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ataeff/g:F16

Run and chat with the model

lemonade run user.g-F16

List all available models

lemonade list

g / wtforacle-plain /README.md

ataeff

Add WTForacle plain voice adapter (train 3.11, eval 3.31)

682f583 verified about 2 months ago

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metadata

base_model: unsloth/gemma-3-270m-it
library_name: peft
pipeline_tag: text-generation
tags:
  - base_model:adapter:unsloth/gemma-3-270m-it
  - lora
  - transformers

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Framework versions

PEFT 0.18.1