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
| FROM python:3.11-slim | |
| WORKDIR /app | |
| # Install system packages needed for some Python wheels | |
| RUN apt-get update && apt-get install -y --no-install-recommends \ | |
| build-essential \ | |
| git \ | |
| && rm -rf /var/lib/apt/lists/* | |
| # Install CPU-only PyTorch first (much smaller than the CUDA version) | |
| RUN pip install --no-cache-dir torch --index-url https://download.pytorch.org/whl/cpu | |
| # Copy and install Python dependencies | |
| COPY requirements.txt . | |
| RUN pip install --no-cache-dir -r requirements.txt | |
| # Copy the rest of the project files | |
| COPY . . | |
| # HuggingFace Spaces expects the app on port 7860 | |
| EXPOSE 7860 | |
| ENV GRADIO_SERVER_NAME=0.0.0.0 | |
| ENV GRADIO_SERVER_PORT=7860 | |
| CMD ["python", "app.py"] | |