Create quent_models.py

quent_models.py

@@ -0,0 +1,47 @@
+
+import os
+from huggingface_hub import hf_hub_download
+from typing import List
+
+def QuantizeModel(model_name: str, lvl: str = 'q4_0'):
+    """
+    Function to quantize the model and save it in GGUF format.
+
+    :param model_name: Path to the model (safetensors file)
+    :param lvl: Quantization level (e.g., 'q4_0')
+    """
+    gguf_name = model_name.replace('.safetensors', f"_{lvl}.gguf")
+    os.system(f'./bin/sd -M convert -m {model_name} -o {gguf_name} -v --type {lvl}')
+
+
+def download_models(models: List[str]):
+    """
+    Download models from Hugging Face using their URLs.
+    
+    :param models: List of Hugging Face model URLs
+    """
+    for model_url in models:
+        os.system(f'curl -L -O {model_url}')
+
+
+# Example usage
+if __name__ == "__main__":
+    models_to_download = [
+        "https://huggingface.co/stabilityai/stable-diffusion-3-medium/resolve/main/sd3_medium_incl_clips_t5xxlfp16.safetensors",
+        "https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt",
+        "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors",
+        "https://huggingface.co/stabilityai/stable-diffusion-2-1/resolve/main/v2-1_768-nonema-pruned.safetensors"
+    ]
+
+    download_models(models_to_download)
+
+    # Quantize models
+    model_names = [
+        'sd-v1-4.ckpt', 
+        'v1-5-pruned-emaonly.safetensors', 
+        'v2-1_768-nonema-pruned.safetensors',
+        'sd3_medium_incl_clips_t5xxlfp16.safetensors'
+    ]
+
+    for model_name in model_names:
+        QuantizeModel(model_name, lvl='q4_0')