- Libraries
- PEFT
How to use shredder-31/Llamma-3_QG_V.2.0 with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "shredder-31/Llamma-3_QG_V.2.0") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use shredder-31/Llamma-3_QG_V.2.0 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 shredder-31/Llamma-3_QG_V.2.0:F16
# Run inference directly in the terminal:
llama cli -hf shredder-31/Llamma-3_QG_V.2.0:F16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf shredder-31/Llamma-3_QG_V.2.0:F16
# Run inference directly in the terminal:
llama cli -hf shredder-31/Llamma-3_QG_V.2.0: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 shredder-31/Llamma-3_QG_V.2.0:F16
# Run inference directly in the terminal:
./llama-cli -hf shredder-31/Llamma-3_QG_V.2.0: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 shredder-31/Llamma-3_QG_V.2.0:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf shredder-31/Llamma-3_QG_V.2.0:F16
Use Docker
docker model run hf.co/shredder-31/Llamma-3_QG_V.2.0:F16
- LM Studio
- Jan
- vLLM
How to use shredder-31/Llamma-3_QG_V.2.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shredder-31/Llamma-3_QG_V.2.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "shredder-31/Llamma-3_QG_V.2.0",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Use Docker
docker model run hf.co/shredder-31/Llamma-3_QG_V.2.0:F16
- Ollama
How to use shredder-31/Llamma-3_QG_V.2.0 with Ollama:
ollama run hf.co/shredder-31/Llamma-3_QG_V.2.0:F16
- Unsloth Studio
How to use shredder-31/Llamma-3_QG_V.2.0 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 shredder-31/Llamma-3_QG_V.2.0 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 shredder-31/Llamma-3_QG_V.2.0 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for shredder-31/Llamma-3_QG_V.2.0 to start chatting
- Docker Model Runner
How to use shredder-31/Llamma-3_QG_V.2.0 with Docker Model Runner:
docker model run hf.co/shredder-31/Llamma-3_QG_V.2.0:F16
- Lemonade
How to use shredder-31/Llamma-3_QG_V.2.0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull shredder-31/Llamma-3_QG_V.2.0:F16
Run and chat with the model
lemonade run user.Llamma-3_QG_V.2.0-F16
List all available models
lemonade list
- Atomic Chat
