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## Usage |
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```python |
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import requests |
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from PIL import Image |
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import torch |
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from transformers import AutoProcessor, LlavaForConditionalGeneration |
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model_id = "nota-ai/phiva-4b-hf" |
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prompt = "USER: <image>\nWhat are these?\nASSISTANT:" |
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image_file = "http://images.cocodataset.org/val2017/000000039769.jpg" |
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model = LlavaForConditionalGeneration.from_pretrained( |
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model_id, |
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torch_dtype=torch.float16, |
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low_cpu_mem_usage=True, |
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attn_implementation="eager" |
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).to(0) |
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processor = AutoProcessor.from_pretrained(model_id) |
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raw_image = Image.open(requests.get(image_file, stream=True).raw) |
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inputs = processor(prompt, raw_image, return_tensors='pt').to(0, torch.float16) |
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output = model.generate(**inputs, max_new_tokens=200, do_sample=False) |
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print(processor.decode(output[0][inputs['input_ids'].shape[-1]:], skip_special_tokens=True)) |
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``` |