Instructions to use chloemeow/flower_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use chloemeow/flower_model with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="chloemeow/flower_model", filename="unsloth.BF16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use chloemeow/flower_model with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf chloemeow/flower_model:BF16 # Run inference directly in the terminal: llama-cli -hf chloemeow/flower_model:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf chloemeow/flower_model:BF16 # Run inference directly in the terminal: llama-cli -hf chloemeow/flower_model:BF16
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 chloemeow/flower_model:BF16 # Run inference directly in the terminal: ./llama-cli -hf chloemeow/flower_model:BF16
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 chloemeow/flower_model:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf chloemeow/flower_model:BF16
Use Docker
docker model run hf.co/chloemeow/flower_model:BF16
- LM Studio
- Jan
- Ollama
How to use chloemeow/flower_model with Ollama:
ollama run hf.co/chloemeow/flower_model:BF16
- Unsloth Studio new
How to use chloemeow/flower_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 chloemeow/flower_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 chloemeow/flower_model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for chloemeow/flower_model to start chatting
- Docker Model Runner
How to use chloemeow/flower_model with Docker Model Runner:
docker model run hf.co/chloemeow/flower_model:BF16
- Lemonade
How to use chloemeow/flower_model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull chloemeow/flower_model:BF16
Run and chat with the model
lemonade run user.flower_model-BF16
List all available models
lemonade list
| FROM ./unsloth.BF16.gguf | |
| # 设置模型格式为 GGUF | |
| PARAMETER format = "gguf" | |
| # 指定模型架构 | |
| PARAMETER family = "llama" | |
| TEMPLATE """你是一位专业的花卉知识助手。请用简洁清晰的语言回答关于花卉的问题,包括花卉的品种、生长习性、养护方法、观赏价值等方面的知识。如果遇到不确定的问题,请诚实地表示无法确定,不要提供错误信息。""" | |