Text Generation
Safetensors
English
llama
prompt-engineering
svg-generation
vector-graphics
prompt-enhancement
lora
unsloth
conversational
Instructions to use kawchar85/SmolLM2-1.7B-Instruct-Prompt-Enhancer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use kawchar85/SmolLM2-1.7B-Instruct-Prompt-Enhancer 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 kawchar85/SmolLM2-1.7B-Instruct-Prompt-Enhancer 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 kawchar85/SmolLM2-1.7B-Instruct-Prompt-Enhancer to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kawchar85/SmolLM2-1.7B-Instruct-Prompt-Enhancer to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="kawchar85/SmolLM2-1.7B-Instruct-Prompt-Enhancer", max_seq_length=2048, )