Instructions to use VoltageVagabond/spam-classifier-liquid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VoltageVagabond/spam-classifier-liquid with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2.5-1.2B-Instruct") model = PeftModel.from_pretrained(base_model, "VoltageVagabond/spam-classifier-liquid") - Notebooks
- Google Colab
- Kaggle
Download launch UI.command from VoltageVagabond/spam-classifier-liquid: direct link, hf CLI and curl.
- Browser
- Download file 465 Bytes
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https://huggingface.co/VoltageVagabond/spam-classifier-liquid/resolve/main/launch%20UI.command
- Command line
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hf download 'hf://VoltageVagabond/spam-classifier-liquid/launch UI.command'
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curl -L -o 'launch UI.command' https://huggingface.co/VoltageVagabond/spam-classifier-liquid/resolve/main/launch%20UI.command
465 Bytes
| cd "$(dirname "$0")" | |
| echo "Starting Liquid AI Spam Classifier..." | |
| echo "" | |
| echo "NOTE: The model takes 30-60 seconds to load into memory." | |
| echo " The browser will open automatically, but the UI won't" | |
| echo " respond until the model is fully loaded." | |
| echo " Watch this terminal for 'Model loaded successfully!'" | |
| echo "" | |
| echo "Opening http://127.0.0.1:7860 in your browser..." | |
| sleep 2 && open http://127.0.0.1:7860 & | |
| venv/bin/python3 app.py | |