Instructions to use medmekk/Llama-3.2-1B-Instruct.GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use medmekk/Llama-3.2-1B-Instruct.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 medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf medmekk/Llama-3.2-1B-Instruct.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 medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf medmekk/Llama-3.2-1B-Instruct.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 medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf medmekk/Llama-3.2-1B-Instruct.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 medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
Use Docker
docker model run hf.co/medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use medmekk/Llama-3.2-1B-Instruct.GGUF with Ollama:
ollama run hf.co/medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
- Unsloth Studio
How to use medmekk/Llama-3.2-1B-Instruct.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 medmekk/Llama-3.2-1B-Instruct.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 medmekk/Llama-3.2-1B-Instruct.GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for medmekk/Llama-3.2-1B-Instruct.GGUF to start chatting
- Pi
How to use medmekk/Llama-3.2-1B-Instruct.GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use medmekk/Llama-3.2-1B-Instruct.GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use medmekk/Llama-3.2-1B-Instruct.GGUF with Docker Model Runner:
docker model run hf.co/medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
- Lemonade
How to use medmekk/Llama-3.2-1B-Instruct.GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Llama-3.2-1B-Instruct.GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use medmekk/Llama-3.2-1B-Instruct.GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default medmekk/Llama-3.2-1B-Instruct.GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
Upload quantized models
Browse files- .gitattributes +20 -0
- Llama-3.2-1B-Instruct-IQ3_M_imat.gguf +3 -0
- Llama-3.2-1B-Instruct-IQ3_XXS_imat.gguf +3 -0
- Llama-3.2-1B-Instruct-IQ4_NL_imat.gguf +3 -0
- Llama-3.2-1B-Instruct-IQ4_XS_imat.gguf +3 -0
- Llama-3.2-1B-Instruct-Q2_K.gguf +3 -0
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- Llama-3.2-1B-Instruct-Q6_K.gguf +3 -0
- Llama-3.2-1B-Instruct-Q8_0.gguf +3 -0
- README.md +34 -0
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# medmekk/Llama-3.2-1B-Instruct.GGUF
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GGUF quantized versions of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct)
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## Available Formats:
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- `Q2_K`: Llama-3.2-1B-Instruct-Q2_K.gguf
|
| 7 |
+
- `Q3_K_S`: Llama-3.2-1B-Instruct-Q3_K_S.gguf
|
| 8 |
+
- `Q3_K_M`: Llama-3.2-1B-Instruct-Q3_K_M.gguf
|
| 9 |
+
- `Q3_K_L`: Llama-3.2-1B-Instruct-Q3_K_L.gguf
|
| 10 |
+
- `Q4_0`: Llama-3.2-1B-Instruct-Q4_0.gguf
|
| 11 |
+
- `Q4_K_S`: Llama-3.2-1B-Instruct-Q4_K_S.gguf
|
| 12 |
+
- `Q4_K_M`: Llama-3.2-1B-Instruct-Q4_K_M.gguf
|
| 13 |
+
- `Q5_0`: Llama-3.2-1B-Instruct-Q5_0.gguf
|
| 14 |
+
- `Q5_K_S`: Llama-3.2-1B-Instruct-Q5_K_S.gguf
|
| 15 |
+
- `Q5_K_M`: Llama-3.2-1B-Instruct-Q5_K_M.gguf
|
| 16 |
+
- `Q6_K`: Llama-3.2-1B-Instruct-Q6_K.gguf
|
| 17 |
+
- `Q8_0`: Llama-3.2-1B-Instruct-Q8_0.gguf
|
| 18 |
+
- `IQ3_M_IMAT`: Llama-3.2-1B-Instruct-IQ3_M_imat.gguf
|
| 19 |
+
- `IQ3_XXS_IMAT`: Llama-3.2-1B-Instruct-IQ3_XXS_imat.gguf
|
| 20 |
+
- `Q4_K_M_IMAT`: Llama-3.2-1B-Instruct-Q4_K_M_imat.gguf
|
| 21 |
+
- `Q4_K_S_IMAT`: Llama-3.2-1B-Instruct-Q4_K_S_imat.gguf
|
| 22 |
+
- `IQ4_NL_IMAT`: Llama-3.2-1B-Instruct-IQ4_NL_imat.gguf
|
| 23 |
+
- `IQ4_XS_IMAT`: Llama-3.2-1B-Instruct-IQ4_XS_imat.gguf
|
| 24 |
+
- `Q5_K_M_IMAT`: Llama-3.2-1B-Instruct-Q5_K_M_imat.gguf
|
| 25 |
+
- `Q5_K_S_IMAT`: Llama-3.2-1B-Instruct-Q5_K_S_imat.gguf
|
| 26 |
+
|
| 27 |
+
## Usage with llama.cpp:
|
| 28 |
+
```bash
|
| 29 |
+
# CLI:
|
| 30 |
+
llama-cli --hf-repo medmekk/Llama-3.2-1B-Instruct.GGUF --hf-file MODEL_FILE -p "Your prompt"
|
| 31 |
+
|
| 32 |
+
# Server:
|
| 33 |
+
llama-server --hf-repo medmekk/Llama-3.2-1B-Instruct.GGUF --hf-file MODEL_FILE -c 2048
|
| 34 |
+
```
|