Instructions to use mradermacher/OpenCoder-8B-Base-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/OpenCoder-8B-Base-i1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/OpenCoder-8B-Base-i1-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/OpenCoder-8B-Base-i1-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 mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/OpenCoder-8B-Base-i1-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 mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/OpenCoder-8B-Base-i1-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 mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/OpenCoder-8B-Base-i1-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 mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/OpenCoder-8B-Base-i1-GGUF with Ollama:
ollama run hf.co/mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mradermacher/OpenCoder-8B-Base-i1-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/OpenCoder-8B-Base-i1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/OpenCoder-8B-Base-i1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.OpenCoder-8B-Base-i1-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download OpenCoder-8B-Base.i1-Q2_K.gguf from mradermacher/OpenCoder-8B-Base-i1-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 3.02 GB
-
https://huggingface.co/mradermacher/OpenCoder-8B-Base-i1-GGUF/resolve/edace96a9bc5a476830bd84683358ff92f12eb1b/OpenCoder-8B-Base.i1-Q2_K.gguf
- Command line
-
hf download hf://mradermacher/OpenCoder-8B-Base-i1-GGUF@edace96a9bc5a476830bd84683358ff92f12eb1b/OpenCoder-8B-Base.i1-Q2_K.gguf
-
curl -L -o OpenCoder-8B-Base.i1-Q2_K.gguf https://huggingface.co/mradermacher/OpenCoder-8B-Base-i1-GGUF/resolve/edace96a9bc5a476830bd84683358ff92f12eb1b/OpenCoder-8B-Base.i1-Q2_K.gguf
3.02 GB
- Xet hash:
- 803f3a873743409121b1ab9f0f67b402024f834b4216c5c3802b86640b2a9d19
- Size of remote file:
- 3.02 GB
- SHA256:
- ed8be369fb33a21a047c317aa841e0805e61205159a7a02e05790530b27a2cb7
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