Instructions to use msj9817/GenHancer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msj9817/GenHancer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="msj9817/GenHancer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("msj9817/GenHancer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
update evaluation codes
Browse files
evaluation/evaluate_mmvp_MetaCLIP_huge.py
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import os
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import clip
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from clip import load
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import csv
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from PIL import Image
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import torch
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import os
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import csv
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from PIL import Image
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import torch
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evaluation/evaluate_mmvp_MetaCLIP_large.py
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import os
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import clip
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from clip import load
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import CLIPVisionModel, CLIPModel, CLIPImageProcessor, CLIPTokenizer
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import argparse
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def benchmark_model(processor, tokenizer, model, benchmark_dir, device="cpu"):
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import os
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import CLIPVisionModel, CLIPModel, CLIPImageProcessor, CLIPTokenizer
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def benchmark_model(processor, tokenizer, model, benchmark_dir, device="cpu"):
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evaluation/evaluate_mmvp_OpenAICLIP_224.py
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import os
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import clip
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from clip import load
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import CLIPVisionModel, CLIPModel, CLIPImageProcessor, CLIPTokenizer
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import argparse
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import os
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import CLIPVisionModel, CLIPModel, CLIPImageProcessor, CLIPTokenizer
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evaluation/evaluate_mmvp_OpenAICLIP_336.py
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import os
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import clip
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from clip import load
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import CLIPVisionModel, CLIPModel, CLIPImageProcessor, CLIPTokenizer
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import argparse
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import os
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import CLIPVisionModel, CLIPModel, CLIPImageProcessor, CLIPTokenizer
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evaluation/evaluate_mmvp_SigLIP_224.py
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import clip
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from clip import load
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import SiglipProcessor, SiglipModel, SiglipImageProcessor, SiglipTokenizer
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import argparse
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import os
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import csv
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from PIL import Image
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import torch
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from tqdm import tqdm
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import json
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from transformers import SiglipProcessor, SiglipModel, SiglipImageProcessor, SiglipTokenizer
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evaluation/evaluate_mmvp_SigLIP_384.py
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import clip
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import csv
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from PIL import Image
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import torch
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import os
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import csv
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from PIL import Image
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import torch
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