BLIP2 (blip2-flan-t5-xxl)

BLIP2 is a visual language model (VLM) that can perform multi-modal tasks such as image captioning and visual question answering. This model is the BLIP-2, Flan-T5-XXL variant.

Intended Use

BLIP2 is a visual language model (VLM) that can perform multi-modal tasks such as image captioning and visual question answering. It can also be used for chat-like conversations by feeding the image and the previous conversation as prompt to the model.

Performance

Best performance within the BLIP2 family of models.

Limitations

BLIP2 is fine-tuned on image-text datasets (e.g. LAION) collected from the internet. As a result the model itself is potentially vulnerable to generating equivalently inappropriate content or replicating inherent biases in the underlying data. Other limitations include:

• May struggle with highly abstract or culturally specific visual concepts

• Performance can vary based on image quality and complexity

• Limited by the training data of its component models (vision encoder and language model)

• Cannot generate or edit images (only processes and describes them)

• Requires careful prompt engineering for optimal performance in some tasks

Citation

Li, J., Li, D., Savarese, S., & Hoi, S. (2023). Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. arXiv preprint arXiv:2301.12597.