instructblip-vicuna-7b

Model overview

InstructBLIP model using Vicuna-7b as language model. InstructBLIP was introduced in the paper InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning by Dai et al. 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. This release is for research purposes only in support of an academic paper. Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes. We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model. We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting use cases, particularly for high-risk scenarios where errors or misuse could significantly impact people’s lives, rights, or safety. For further guidance on use cases, refer to our AUP and AI AUP.

Key features

特点摘要待依据来源补齐，不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

Frequently asked questions

Sources & traceability

许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。