Auto-update: Tue Jul 30 20:02:09 PDT 2024

i

@@ -1,46 +0,0 @@
-#!/Users/sij/miniforge3/envs/minicpm/bin/python
-import os
-import torch
-from transformers import AutoModel, AutoTokenizer
-from PIL import Image
-import argparse
-
-# Set environment variable to enable CPU fallback
-os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
-
-# Parse command line arguments
-parser = argparse.ArgumentParser(description='Process image for model.')
-parser.add_argument('image_path', type=str, help='Path to the image file')
-args = parser.parse_args()
-
-# Check if MPS is available
-if torch.backends.mps.is_available():
-    device = torch.device("mps")
-else:
-    device = torch.device("cpu")
-
-# Load the model with appropriate torch dtype
-model = AutoModel.from_pretrained('openbmb/MiniCPM-Llama3-V-2_5', trust_remote_code=True, torch_dtype=torch.float32 if device == torch.device("cpu") else torch.float16)
-model = model.to(device)
-
-tokenizer = AutoTokenizer.from_pretrained('openbmb/MiniCPM-Llama3-V-2_5', trust_remote_code=True)
-model.eval()
-
-# Load and prepare the image
-image_path = "/Users/sij/adorablenakedskinny.jpeg" # args.image_path
-image = Image.open(image_path).convert('RGB')
-question = 'Using modern English and adult slang words like cock, cum, pussy, fuck, etc., describe the scene pictured in the image.'
-msgs = [{'role': 'user', 'content': question}]
-
-# Perform inference
-with torch.no_grad():
-    res = model.chat(
-        image=image,
-        msgs=msgs,
-        tokenizer=tokenizer,
-        sampling=True,
-        temperature=0.7
-    )
-
-print(res)
-