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README.md
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@@ -230,10 +230,10 @@ def load_image(image_file):
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return image
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config = AutoConfig.from_pretrained("
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tokenizer = AutoTokenizer.from_pretrained("
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processor = AutoProcessor.from_pretrained("
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model = AutoModelForCausalLM.from_pretrained("
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model.eval()
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# For single image and text
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| MLP | 6.3M | 2 | - | 2048 | - |
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| LM | 1.2B | 16 | 16 | 2048 | - |
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We initialize the vision encoder from [CLIP-ViT-L/14@336](https://huggingface.co/openai/clip-vit-large-patch14-336) and initialize LM from [AMD OLMo 1B SFT](https://huggingface.co/
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## Training Stages
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return image
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config = AutoConfig.from_pretrained("amd/Instella-VL-1B", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("amd/Instella-VL-1B", config=config, trust_remote_code=True)
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processor = AutoProcessor.from_pretrained("amd/Instella-VL-1B", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("amd/Instella-VL-1B", trust_remote_code=True).to('cuda') # or 'cpu'
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model.eval()
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# For single image and text
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| MLP | 6.3M | 2 | - | 2048 | - |
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| LM | 1.2B | 16 | 16 | 2048 | - |
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We initialize the vision encoder from [CLIP-ViT-L/14@336](https://huggingface.co/openai/clip-vit-large-patch14-336) and initialize LM from [AMD OLMo 1B SFT](https://huggingface.co/amd/AMD-OLMo-1B-SFT)
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## Training Stages
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