Instructions to use tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-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 tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-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 tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama cli -hf tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
- Llama new
- LM Studio
- Jan
- Ollama
How to use tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF with Ollama:
ollama run hf.co/tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
- Lemonade
How to use tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF:Q2_K
Run and chat with the model
lemonade run user.yeontaek_WizardCoder-Python-13B-LoRa-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Download WizardCoder-Python-13B-LoRa-Q4_0.gguf from tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 7.37 GB
-
https://huggingface.co/tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF/resolve/0c166ecaaa89830cccd0b5a6ecc3d06bc81d06a3/WizardCoder-Python-13B-LoRa-Q4_0.gguf
- Command line
-
hf download hf://tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF@0c166ecaaa89830cccd0b5a6ecc3d06bc81d06a3/WizardCoder-Python-13B-LoRa-Q4_0.gguf
-
curl -L -o WizardCoder-Python-13B-LoRa-Q4_0.gguf https://huggingface.co/tensorblock/yeontaek_WizardCoder-Python-13B-LoRa-GGUF/resolve/0c166ecaaa89830cccd0b5a6ecc3d06bc81d06a3/WizardCoder-Python-13B-LoRa-Q4_0.gguf
7.37 GB
- Xet hash:
- d78cf3c213d90ca78fe1c5ae1739186ed5818ce82d679371fd6304e577b513a0
- Size of remote file:
- 7.37 GB
- SHA256:
- 0f04c8493f0217a06118d594216425992f53566a94c998e39efc566e5922c235
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