Instructions to use TheBloke/Llama-2-Coder-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/Llama-2-Coder-7B-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/Llama-2-Coder-7B-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheBloke/Llama-2-Coder-7B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use TheBloke/Llama-2-Coder-7B-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 TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TheBloke/Llama-2-Coder-7B-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 TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TheBloke/Llama-2-Coder-7B-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 TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf TheBloke/Llama-2-Coder-7B-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 TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use TheBloke/Llama-2-Coder-7B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/Llama-2-Coder-7B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Llama-2-Coder-7B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M
- SGLang
How to use TheBloke/Llama-2-Coder-7B-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TheBloke/Llama-2-Coder-7B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Llama-2-Coder-7B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "TheBloke/Llama-2-Coder-7B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Llama-2-Coder-7B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use TheBloke/Llama-2-Coder-7B-GGUF with Ollama:
ollama run hf.co/TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use TheBloke/Llama-2-Coder-7B-GGUF with Docker Model Runner:
docker model run hf.co/TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M
- Lemonade
How to use TheBloke/Llama-2-Coder-7B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TheBloke/Llama-2-Coder-7B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Llama-2-Coder-7B-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Update base_model formatting
Browse files
README.md
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base_model: https://huggingface.co/mrm8488/llama-2-coder-7b
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datasets:
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inference: false
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language:
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license: apache-2.0
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model_creator: mrm8488
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model_name: Llama 2 Coder 7B
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model_type: llama
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pipeline_tag: text-generation
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prompt_template: 'You are a coding assistant that will help the user to resolve the
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quantized_by: TheBloke
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tags:
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- code
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- coding
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- llama
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thumbnail: https://huggingface.co/mrm8488/llama-2-coder-7b/resolve/main/llama2-coder-logo-removebg-preview.png
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language:
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license: apache-2.0
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tags:
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- generated_from_trainer
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- code
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- coding
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- llama
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datasets:
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- HuggingFaceH4/CodeAlpaca_20K
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base_model: mrm8488/llama-2-coder-7b
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inference: false
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model_creator: mrm8488
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model_type: llama
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pipeline_tag: text-generation
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prompt_template: 'You are a coding assistant that will help the user to resolve the
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quantized_by: TheBloke
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thumbnail: https://huggingface.co/mrm8488/llama-2-coder-7b/resolve/main/llama2-coder-logo-removebg-preview.png
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model-index:
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- name: FalCoder
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results: []
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