InternViT-6B-448px-V2_5
Enhanced visual model based on InternViT-6B-448px-V1-5
Product Details
InternViT-6B-448px-V2_5 is a visual model based on InternViT-6B-448px-V1-5. By using ViT incremental learning with NTP loss (stage 1.5), it improves the visual encoder's ability to extract visual features, especially in areas that are underrepresented in large-scale network datasets, such as multi-language OCR data and mathematical charts. This model is part of the InternVL 2.5 series, retaining the same "ViT-MLP-LLM" model architecture as the previous generation, and integrating the new incremental pre-trained InternViT with various pre-trained LLMs, including InternLM 2.5 and Qwen 2.5, using randomly initialized MLP projectors.
Main Features
How to Use
Target Users
The target audience is researchers, developers and enterprises, especially those who need to handle tasks such as image recognition, classification and semantic segmentation. Due to the model's advantages in multi-lingual OCR and mathematical chart recognition, it is also suitable for educational institutions and academic researchers who need to process data in these specific fields.
Examples
Case 1: Use InternViT-6B-448px-V2_5 for image classification and identify the main objects in the image.
Case 2: In multi-language document processing, the model is used to identify and convert OCR data.
Case 3: In the field of education, models are used to identify and analyze mathematical diagrams to assist teaching and learning.
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