Instructions to use Ashraya/gemma-270m-legal-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Ashraya/gemma-270m-legal-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Ashraya/gemma-270m-legal-gguf", filename="gemma-270m-q4km-optimized.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Ashraya/gemma-270m-legal-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Ashraya/gemma-270m-legal-gguf # Run inference directly in the terminal: llama-cli -hf Ashraya/gemma-270m-legal-gguf
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Ashraya/gemma-270m-legal-gguf # Run inference directly in the terminal: llama-cli -hf Ashraya/gemma-270m-legal-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 Ashraya/gemma-270m-legal-gguf # Run inference directly in the terminal: ./llama-cli -hf Ashraya/gemma-270m-legal-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 Ashraya/gemma-270m-legal-gguf # Run inference directly in the terminal: ./build/bin/llama-cli -hf Ashraya/gemma-270m-legal-gguf
Use Docker
docker model run hf.co/Ashraya/gemma-270m-legal-gguf
- LM Studio
- Jan
- Ollama
How to use Ashraya/gemma-270m-legal-gguf with Ollama:
ollama run hf.co/Ashraya/gemma-270m-legal-gguf
- Unsloth Studio
How to use Ashraya/gemma-270m-legal-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 Ashraya/gemma-270m-legal-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 Ashraya/gemma-270m-legal-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Ashraya/gemma-270m-legal-gguf to start chatting
- Docker Model Runner
How to use Ashraya/gemma-270m-legal-gguf with Docker Model Runner:
docker model run hf.co/Ashraya/gemma-270m-legal-gguf
- Lemonade
How to use Ashraya/gemma-270m-legal-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Ashraya/gemma-270m-legal-gguf
Run and chat with the model
lemonade run user.gemma-270m-legal-gguf-{{QUANT_TAG}}List all available models
lemonade list
Gemma 3 270M - Legal Auto-Completion (GGUF)
Fine-tuned Gemma 3 270M for legal text auto-completion, optimized for client-side browser deployment.
Model Details
- Format: GGUF (Q4_K_M quantization with Q5_0 fallback)
- Size: ~169 MB
- Optimized for: Wllama (WebAssembly) browser inference
Usage with llama.cpp
./llama-cli -m gemma-270m-q4km-optimized.gguf -p "The court held that" -n 30
Usage with Wllama (Browser)
import { Wllama } from '@wllama/wllama';
const CONFIG_PATHS = {
'single-thread/wllama.wasm': 'path/to/single-thread/wllama.wasm',
'multi-thread/wllama.wasm': 'path/to/multi-thread/wllama.wasm',
};
const wllama = new Wllama(CONFIG_PATHS);
await wllama.loadModelFromHF(
'Ashraya/gemma-270m-legal-gguf',
'gemma-270m-q4km-optimized.gguf'
);
const result = await wllama.createCompletion('The court held that', {
nPredict: 20,
sampling: { temp: 0.3, top_p: 0.95 }
});
console.log(result);
Files
gemma-270m-q4km-optimized.gguf- Main model file (~169MB)
- Downloads last month
- 2
Hardware compatibility
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docker model run hf.co/Ashraya/gemma-270m-legal-gguf