Instructions to use Baskar2005/deepseek_Sunfall_Merged_Model 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 Baskar2005/deepseek_Sunfall_Merged_Model 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 Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M # Run inference directly in the terminal: llama cli -hf Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M # Run inference directly in the terminal: llama cli -hf Baskar2005/deepseek_Sunfall_Merged_Model: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 Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Baskar2005/deepseek_Sunfall_Merged_Model: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 Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M
Use Docker
docker model run hf.co/Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Baskar2005/deepseek_Sunfall_Merged_Model with Ollama:
ollama run hf.co/Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M
- Unsloth Studio
How to use Baskar2005/deepseek_Sunfall_Merged_Model with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Baskar2005/deepseek_Sunfall_Merged_Model to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Baskar2005/deepseek_Sunfall_Merged_Model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Baskar2005/deepseek_Sunfall_Merged_Model to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Baskar2005/deepseek_Sunfall_Merged_Model with Docker Model Runner:
docker model run hf.co/Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M
- Lemonade
How to use Baskar2005/deepseek_Sunfall_Merged_Model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Baskar2005/deepseek_Sunfall_Merged_Model:Q4_K_M
Run and chat with the model
lemonade run user.deepseek_Sunfall_Merged_Model-Q4_K_M
List all available models
lemonade list
| license: apache-2.0 | |
| tags: | |
| - gguf | |
| - llama.cpp | |
| - quantized | |
| - deepseek | |
| - stheno | |
| # DeepSeek Sunfall Merged - GGUF Quantized Models | |
| This repository contains multiple **quantized GGUF variants** of the merged DeepSeek + Sunfall model, compatible with `llama.cpp`. | |
| ## 🧠 Available Quantized Formats | |
| | Format | File Name | Description | | |
| |-------------|--------------------------------------------------|---------------------------------| | |
| | Q3_K_M | `deepseek_sunfall_merged_Model.Q3_K_M.gguf` | Smallest size, fastest inference | | |
| | Q4_K_M | `deepseek_sunfall_merged_Model.Q4_K_M.gguf` | Balanced speed & performance | | |
| | Q5_K_M | `deepseek_sunfall_merged_Model.Q5_K_M.gguf` | Better quality, slower | | |
| | Q6_K | `deepseek_sunfall_merged_Model.Q6_K.gguf` | Near full precision | | |
| | Q8_0 | `deepseek_sunfall_merged_Model.Q8_0.gguf` | Almost no compression loss | | |
| ## 🔧 Usage (Python) | |
| Install `llama-cpp-python`: | |
| ```bash | |
| pip install llama-cpp-python | |
| from llama_cpp import Llama | |
| model = Llama(model_path="deepseek_sunfall_merged_Model.Q4_K_M.gguf") # or Q3_K_M, etc. | |
| output = model("Tell me a story about stars.") | |
| print(output)``` |