Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+metrics:
+- accuracy
+base_model:
+- liuhaotian/llava-v1.6-mistral-7b
+pipeline_tag: image-classification
+library_name: transformers
+tags:
+- llm
+- mllm
+- deepfake
+---
+# FFAA Model Card
+## Model details
+**Model type**: Face Forgery Analysis Assistant (FFAA) consists of a fine-tuned MLLM and Multi-answer Intelligent Decision System (MIDS).
+It is a Multi-modal Large Language Model dedicated to the face forgery analysis.
+Base MLLM: [liuhaotian/llava-v1.6-mistral-7b](https://huggingface.co/liuhaotian/llava-v1.6-mistral-7b)
+
+**Paper or resources for more information**: [https://ffaa-vl.github.io/](https://ffaa-vl.github.io/)
+
+**Where to send questions or comments about the model**: [https://github.com/thu-huangzc/FFAA/issues](https://github.com/thu-huangzc/FFAA/issues)
+
+## Intended use
+**Primary intended uses**: The primary use of FFAA is research on the applications of MLLMs in face forgery analysis, which is essential
+for understanding the model’s decision-making process and advancing real-world face forgery analysis.
+
+**Primary intended users**: The primary intended users of the model are researchers and hobbyists in computer vision, 
+natural language processing, machine learning, and artificial intelligence.
+
+## Training dataset
+* 20K face forgery analysis VQA (FFA-VQA) dataset, captioned by GPT-4o.
+
+* 90K historical answer data generated by the MLLM fine-tuned on FFA-VQA.
+
+## Evaluation dataset
+Open-World Face Forgery Analysis Benchmark (OW-FFA-Bench), including 6 face forgery generalization test sets. 
+The download link is [Google driver](https://drive.google.com/file/d/1867ZKwFCh_OLm-uUsiIiI9RjrUv0JMZX/view?usp=drive_link)