Update README.md
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README.md
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@@ -55,12 +55,19 @@ from transformers import AutoModel, CLIPImageProcessor
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from transformers import AutoTokenizer
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path = "OpenGVLab/InternVL-Chat-Chinese-V1-1"
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model = AutoModel.from_pretrained(
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path,
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torch_dtype=torch.bfloat16,
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low_cpu_mem_usage=True,
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trust_remote_code=True
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tokenizer = AutoTokenizer.from_pretrained(path)
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image = Image.open('./examples/image2.jpg').convert('RGB')
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from transformers import AutoTokenizer
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path = "OpenGVLab/InternVL-Chat-Chinese-V1-1"
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# If your GPU has more than 40G memory, you can put the entire model on a single GPU.
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model = AutoModel.from_pretrained(
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path,
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torch_dtype=torch.bfloat16,
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low_cpu_mem_usage=True,
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trust_remote_code=True).eval().cuda()
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# Otherwise, you need to set device_map='auto' to use multiple GPUs for inference.
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# model = AutoModel.from_pretrained(
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# path,
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# torch_dtype=torch.bfloat16,
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# low_cpu_mem_usage=True,
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# trust_remote_code=True,
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# device_map='auto').eval()
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tokenizer = AutoTokenizer.from_pretrained(path)
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image = Image.open('./examples/image2.jpg').convert('RGB')
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