Instructions to use trollek/SmolImagePromptHelper-135M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trollek/SmolImagePromptHelper-135M-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trollek/SmolImagePromptHelper-135M-GGUF", dtype="auto") - llama-cpp-python
How to use trollek/SmolImagePromptHelper-135M-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="trollek/SmolImagePromptHelper-135M-GGUF", filename="SmolImagePromptHelper-135M_F16.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 trollek/SmolImagePromptHelper-135M-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf trollek/SmolImagePromptHelper-135M-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf trollek/SmolImagePromptHelper-135M-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf trollek/SmolImagePromptHelper-135M-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf trollek/SmolImagePromptHelper-135M-GGUF:F16
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 trollek/SmolImagePromptHelper-135M-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf trollek/SmolImagePromptHelper-135M-GGUF:F16
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 trollek/SmolImagePromptHelper-135M-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf trollek/SmolImagePromptHelper-135M-GGUF:F16
Use Docker
docker model run hf.co/trollek/SmolImagePromptHelper-135M-GGUF:F16
- LM Studio
- Jan
- Ollama
How to use trollek/SmolImagePromptHelper-135M-GGUF with Ollama:
ollama run hf.co/trollek/SmolImagePromptHelper-135M-GGUF:F16
- Unsloth Studio new
How to use trollek/SmolImagePromptHelper-135M-GGUF 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 trollek/SmolImagePromptHelper-135M-GGUF 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 trollek/SmolImagePromptHelper-135M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for trollek/SmolImagePromptHelper-135M-GGUF to start chatting
- Docker Model Runner
How to use trollek/SmolImagePromptHelper-135M-GGUF with Docker Model Runner:
docker model run hf.co/trollek/SmolImagePromptHelper-135M-GGUF:F16
- Lemonade
How to use trollek/SmolImagePromptHelper-135M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull trollek/SmolImagePromptHelper-135M-GGUF:F16
Run and chat with the model
lemonade run user.SmolImagePromptHelper-135M-GGUF-F16
List all available models
lemonade list
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)Smol Image Prompt Helper
Quants of SmolImagePromptHelper-135M
Model description
Lets say you have a node in ComfyUI to parse JSON and send the appropriate prompt to the text encoders. Tadaaa:
You are an AI assistant tasked with expanding and formatting image prompts. You are given an input that you will need to write image prompts for different text encoders.
Always respond with the following format:
{
"clip_l": "<keywords from image analysis>",
"clip_g": "<simple descriptions of the image>",
"t5xxl": "<complex semanticly rich description of the image>",
"negative": "<contrasting keywords for what is not in the image>"
}
Intended uses & limitations
Have a look at the dataset that I created (ImagePromptHelper-v02 (CC BY 4.0)) and you will see whaaaaat I've doooone.
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Model tree for trollek/SmolImagePromptHelper-135M-GGUF
Base model
HuggingFaceTB/SmolLM2-135M
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="trollek/SmolImagePromptHelper-135M-GGUF", filename="", )