Instructions to use P0x0/Astra-v1-12B-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 P0x0/Astra-v1-12B-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 P0x0/Astra-v1-12B-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf P0x0/Astra-v1-12B-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf P0x0/Astra-v1-12B-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf P0x0/Astra-v1-12B-GGUF:Q4_0
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 P0x0/Astra-v1-12B-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf P0x0/Astra-v1-12B-GGUF:Q4_0
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 P0x0/Astra-v1-12B-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf P0x0/Astra-v1-12B-GGUF:Q4_0
Use Docker
docker model run hf.co/P0x0/Astra-v1-12B-GGUF:Q4_0
- LM Studio
- Jan
- vLLM
How to use P0x0/Astra-v1-12B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "P0x0/Astra-v1-12B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "P0x0/Astra-v1-12B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/P0x0/Astra-v1-12B-GGUF:Q4_0
- Ollama
How to use P0x0/Astra-v1-12B-GGUF with Ollama:
ollama run hf.co/P0x0/Astra-v1-12B-GGUF:Q4_0
- Unsloth Desktop
- Docker Model Runner
How to use P0x0/Astra-v1-12B-GGUF with Docker Model Runner:
docker model run hf.co/P0x0/Astra-v1-12B-GGUF:Q4_0
- Lemonade
How to use P0x0/Astra-v1-12B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull P0x0/Astra-v1-12B-GGUF:Q4_0
Run and chat with the model
lemonade run user.Astra-v1-12B-GGUF-Q4_0
List all available models
lemonade list
- Atomic Chat
Astra-v1-12B
Astra-v1-12B is a fine-tuned version of the base model Mistral-Nemo-Base-2407, developed for general-purpose natural language processing tasks. It was fine-tuned to replicate the quality and style of Claude 3's Sonnet and Opus models.
Model Description
Astra-v1-12B is a general-purpose transformer-based language model fine-tuned for instruction-following tasks. The fine-tuning was designed to match the high-quality generation seen in Claude 3's Sonnet and Opus models, optimized for tasks such as text generation, summarization, question answering, and more.
- Developed by: P0x0
- Finetuned from: Mistral-Nemo-Base-2407
- License: Apache 2.0
Model Sources
- Repository: https://huggingface.co/P0x0/astra-v1-12b
Uses
Direct Use
Astra-v1-12B can be used directly for a wide range of NLP tasks, including:
- Text generation
- Summarization
- Question answering
- Dialogue systems
Out-of-Scope Use
Astra-v1-12B is not intended for real-time decision-making in critical applications or generating harmful or biased content.
How to Get Started with the quantized model
To run the quantized version of the model, you can use KoboldCPP, which allows you to run quantized GGUF models locally.
I encourage you to provide feedback on the model's performance. If you'd like to create your own quantizations, feel free to do so and let me know how it works for you!
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