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
| # ============================================================= | |
| # Spam Classifier — Rebuild GGUF + Reload Server | |
| # Run this after retraining to bake the new adapter into | |
| # spam-classifier-F16.gguf and reload the llama.cpp server. | |
| # ============================================================= | |
| LIQUID_DIR="$(cd "$(dirname "$0")" && pwd)" | |
| PROJ_DIR="$(dirname "$LIQUID_DIR")" | |
| GGUF_FILE="$PROJ_DIR/spam-classifier-F16.gguf" | |
| MERGED_DIR="$PROJ_DIR/merged-liquid-full" | |
| echo "============================================================" | |
| echo " Spam Classifier — Rebuild GGUF" | |
| echo "============================================================" | |
| echo "" | |
| echo " Adapter: $LIQUID_DIR/adapters" | |
| echo " Output: $PROJ_DIR/spam-classifier-F16.gguf" | |
| echo "" | |
| # ── Check adapter exists ── | |
| if [[ ! -d "$LIQUID_DIR/adapters" ]]; then | |
| echo " ERROR: No adapter found at $LIQUID_DIR/adapters/" | |
| echo " Run retrain.command first." | |
| echo "" | |
| read -n 1 -s -r -p "Press any key to close..." | |
| exit 1 | |
| fi | |
| # ── Remove cached merge so new adapter is actually baked in ── | |
| if [[ -d "$MERGED_DIR" ]]; then | |
| echo " Removing cached merged model (so new adapter is used)..." | |
| rm -rf "$MERGED_DIR" | |
| echo " Done." | |
| echo "" | |
| fi | |
| # ── Run merge + GGUF conversion ── | |
| echo " Merging adapter into base model and converting to GGUF..." | |
| echo " (This takes ~5-10 minutes and uses ~8 GB of RAM)" | |
| echo "" | |
| cd "$PROJ_DIR" | |
| source "$LIQUID_DIR/venv/bin/activate" | |
| python3 merge_and_convert_gguf.py | |
| BUILD_STATUS=$? | |
| deactivate | |
| echo "" | |
| if [[ $BUILD_STATUS -ne 0 ]]; then | |
| echo " ERROR: GGUF build failed (exit $BUILD_STATUS)." | |
| echo "" | |
| read -n 1 -s -r -p "Press any key to close..." | |
| exit 1 | |
| fi | |
| GGUF_SIZE_MB=$(du -m "$GGUF_FILE" 2>/dev/null | cut -f1) | |
| echo " GGUF rebuilt: spam-classifier-F16.gguf (${GGUF_SIZE_MB} MB)" | |
| echo "" | |
| # ── Upload to HuggingFace ── | |
| echo "------------------------------------------------------------" | |
| echo " Upload new GGUF to HuggingFace? [y/N] " | |
| read -n 1 -s -r hf_choice | |
| echo "$hf_choice" | |
| echo "" | |
| if [[ "$hf_choice" == "y" || "$hf_choice" == "Y" ]]; then | |
| echo " Uploading spam-classifier-F16.gguf..." | |
| python3 - <<PYEOF | |
| from huggingface_hub import HfApi | |
| api = HfApi() | |
| import os | |
| gguf_file = "$GGUF_FILE" | |
| repo_id = "VoltageVagabond/spam-classifier-liquid-GGUF" | |
| print(f" Uploading to {repo_id}...") | |
| api.upload_file( | |
| path_or_fileobj=gguf_file, | |
| path_in_repo="spam-classifier-F16.gguf", | |
| repo_id=repo_id, | |
| repo_type="model", | |
| commit_message="Rebuild GGUF after full retrain", | |
| ) | |
| print(f" Done! https://huggingface.co/{repo_id}") | |
| PYEOF | |
| echo "" | |
| fi | |
| # ── Remind to restart server ── | |
| echo "============================================================" | |
| echo " Done! To load the new model into llama.cpp:" | |
| echo "" | |
| echo " 1. Double-click StopServer.command" | |
| echo " 2. Double-click StartServer.command" | |
| echo "============================================================" | |
| echo "" | |
| read -n 1 -s -r -p "Press any key to close..." | |