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--- |
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language: en |
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license: other |
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tags: |
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- vision |
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- image-captioning |
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pipeline_tag: image-text-to-text |
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--- |
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# InstructBLIP model |
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InstructBLIP model using [Vicuna-13b](https://github.com/lm-sys/FastChat#model-weights) as language model. InstructBLIP was introduced in the paper [InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning](https://arxiv.org/abs/2305.06500) by Dai et al. |
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Disclaimer: The team releasing InstructBLIP did not write a model card for this model so this model card has been written by the Hugging Face team. |
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## Model description |
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InstructBLIP is a visual instruction tuned version of [BLIP-2](https://huggingface.co/docs/transformers/main/model_doc/blip-2). Refer to the paper for details. |
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![InstructBLIP architecture](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/instructblip_architecture.jpg) |
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## Intended uses & limitations |
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Usage is as follows: |
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``` |
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from transformers import InstructBlipProcessor, InstructBlipForConditionalGeneration |
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import torch |
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from PIL import Image |
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import requests |
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model = InstructBlipForConditionalGeneration.from_pretrained("Salesforce/instructblip-vicuna-13b") |
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processor = InstructBlipProcessor.from_pretrained("Salesforce/instructblip-vicuna-13b") |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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model.to(device) |
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url = "https://raw.githubusercontent.com/salesforce/LAVIS/main/docs/_static/Confusing-Pictures.jpg" |
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image = Image.open(requests.get(url, stream=True).raw).convert("RGB") |
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prompt = "What is unusual about this image?" |
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inputs = processor(images=image, text=prompt, return_tensors="pt").to(device) |
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outputs = model.generate( |
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**inputs, |
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do_sample=False, |
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num_beams=5, |
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max_length=256, |
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min_length=1, |
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top_p=0.9, |
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repetition_penalty=1.5, |
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length_penalty=1.0, |
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temperature=1, |
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) |
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generated_text = processor.batch_decode(outputs, skip_special_tokens=True)[0].strip() |
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print(generated_text) |
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``` |
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### How to use |
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For code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/instructblip). |