Instructions to use YorkieOH10/CodeLlama-7B-KStack-Q8_0-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 YorkieOH10/CodeLlama-7B-KStack-Q8_0-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 YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
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 YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
Use Docker
docker model run hf.co/YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF with Ollama:
ollama run hf.co/YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF with Docker Model Runner:
docker model run hf.co/YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
- Lemonade
How to use YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF:Q8_0
Run and chat with the model
lemonade run user.CodeLlama-7B-KStack-Q8_0-GGUF-Q8_0
List all available models
lemonade list
- Atomic Chat
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Download README.md from YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 1.44 kB
-
https://huggingface.co/YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF/resolve/main/README.md
- Command line
-
hf download hf://YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF/README.md
-
curl -L -o README.md https://huggingface.co/YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF/resolve/main/README.md
1.44 kB
metadata
license: apache-2.0
tags:
- code
- llama-cpp
- gguf-my-repo
datasets:
- JetBrains/KStack
results:
- task:
type: text-generation
dataset:
name: MultiPL-HumanEval (Kotlin)
type: openai_humaneval
metrics:
- name: pass@1
type: pass@1
value: 29.19
YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF
This model was converted to GGUF format from JetBrains/CodeLlama-7B-KStack using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI. CLI:
llama-cli --hf-repo YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF --model codellama-7b-kstack-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo YorkieOH10/CodeLlama-7B-KStack-Q8_0-GGUF --model codellama-7b-kstack-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && \
cd llama.cpp && \
make && \
./main -m codellama-7b-kstack-q8_0.gguf -n 128