Instructions to use Breakintelligence/cveparrot 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 Breakintelligence/cveparrot 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 Breakintelligence/cveparrot # Run inference directly in the terminal: llama cli -hf Breakintelligence/cveparrot
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Breakintelligence/cveparrot # Run inference directly in the terminal: llama cli -hf Breakintelligence/cveparrot
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 Breakintelligence/cveparrot # Run inference directly in the terminal: ./build/bin/llama cli -hf Breakintelligence/cveparrot
Use Docker
docker model run hf.co/Breakintelligence/cveparrot
- Llama new
- LM Studio
- Jan
- vLLM
How to use Breakintelligence/cveparrot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Breakintelligence/cveparrot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Breakintelligence/cveparrot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Breakintelligence/cveparrot
- Ollama
How to use Breakintelligence/cveparrot with Ollama:
ollama run hf.co/Breakintelligence/cveparrot
- Unsloth Desktop
- Docker Model Runner
How to use Breakintelligence/cveparrot with Docker Model Runner:
docker model run hf.co/Breakintelligence/cveparrot
- Lemonade
How to use Breakintelligence/cveparrot with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Breakintelligence/cveparrot
Run and chat with the model
lemonade run user.cveparrot-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Commit ·
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Parent(s): bcf9192
Update Ollama instructions - users need to download GGUF and create local model
Browse files
README.md
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@@ -131,17 +131,36 @@ brew install ollama
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# Or download from https://ollama.com
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```
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**Step 2:
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```bash
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#
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ollama
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# Interactive mode
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ollama run
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# Single query
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ollama run
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```
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**Using Ollama API (Python):**
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# Generate response
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response = ollama.generate(
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model='cveparrot',
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prompt='Describe the security vulnerability CVE-2024-1234',
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)
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# Or download from https://ollama.com
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```
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**Step 2: Download the GGUF Model**
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Download `cveparrot.gguf` from the [Files section](https://huggingface.co/Prachir-AI/cveparrot/tree/main) of this repository.
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**Step 3: Create a Modelfile**
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Create a file named `Modelfile` in the same directory as the downloaded GGUF:
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```
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FROM ./cveparrot.gguf
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TEMPLATE """{{ .Prompt }}"""
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PARAMETER temperature 0.7
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PARAMETER top_p 0.9
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PARAMETER top_k 40
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PARAMETER num_ctx 2048
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```
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**Step 4: Create and Run the Model**
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```bash
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# Create the model in Ollama
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ollama create cveparrot -f Modelfile
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# Interactive mode
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ollama run cveparrot
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# Single query
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ollama run cveparrot "Describe CVE-2024-1234"
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```
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**Using Ollama API (Python):**
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# Generate response
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response = ollama.generate(
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model='cveparrot', # Use the local model name you created
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prompt='Describe the security vulnerability CVE-2024-1234',
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)
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