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Update app.py
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app.py
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@@ -14,18 +14,18 @@ from tqdm import tqdm
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from colpali_engine.models import ColQwen2, ColQwen2Processor
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@spaces.GPU
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def install_fa2():
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print("Install FA2")
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os.system("pip install flash-attn --no-build-isolation")
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model = ColQwen2.from_pretrained(
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"vidore/colqwen2-v1.0",
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torch_dtype=torch.bfloat16,
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device_map="cuda:0", # or "mps" if on Apple Silicon
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).eval()
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processor = ColQwen2Processor.from_pretrained("vidore/colqwen2-v1.0")
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@@ -84,7 +84,6 @@ def query_gpt4o_mini(query, images, api_key):
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return "Enter your OpenAI API key to get a custom response"
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@spaces.GPU
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def search(query: str, ds, images, k, api_key):
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k = min(k, len(ds))
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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@@ -124,8 +123,8 @@ def convert_files(files):
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for f in files:
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images.extend(convert_from_path(f, thread_count=4))
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if len(images) >=
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raise gr.Error("The number of images in the dataset should be less than
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return images
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from colpali_engine.models import ColQwen2, ColQwen2Processor
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def install_fa2():
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print("Install FA2")
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os.system("pip install flash-attn --no-build-isolation")
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install_fa2()
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model = ColQwen2.from_pretrained(
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"vidore/colqwen2-v1.0",
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torch_dtype=torch.bfloat16,
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device_map="cuda:0", # or "mps" if on Apple Silicon
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attn_implementation="flash_attention_2", # should work on A100
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).eval()
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processor = ColQwen2Processor.from_pretrained("vidore/colqwen2-v1.0")
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return "Enter your OpenAI API key to get a custom response"
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def search(query: str, ds, images, k, api_key):
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k = min(k, len(ds))
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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for f in files:
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images.extend(convert_from_path(f, thread_count=4))
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if len(images) >= 500:
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raise gr.Error("The number of images in the dataset should be less than 500.")
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return images
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