Model Card for Model ID
Its a Pretrained MultiModal from HuggingFaceM4/idefics2-8b model that accepts arbitrary sequences of image and text inputs and produces text outputs. The model can answer questions about images, describe visual content, create stories grounded on multiple images, or simply behave as a pure language model without visual inputs. It improves upon Idefics1, significantly enhancing capabilities around OCR, document understanding and visual reasoning.
Model Description
Its take as Input as Text and Image and Transforms to Text.
- Developed by: Samim Kumar Patel
- Model type: Multi-modal model (image+text)
- Language(s) (NLP): en
- License: creativeml-openrail-m
- Finetuned from model [optional]: HuggingFaceM4/idefics2-8b
Use Cases
Healthcare Diagnostics:
Using patient medical records and radiographic images, This Model could assist in providing preliminary diagnoses by cross-referencing symptoms (text) with scan images.
Social Media Moderation:
By analyzing textual posts along with associated images, This Model could help identify and flag inappropriate content or misinformation spread across social media platforms.
Retail Customer Experience:
In retail, This Model can enhance the shopping experience by providing product recommendations through analyzing customer reviews (text) and product images.
Autonomous Vehicles:
This Model could be employed in the development of smarter autonomous driving systems that interpret road signs (text) and detect traffic signals or potential hazards (image).
Educational Tools:
For educational software, This Model could offer more interactive learning experiences by correlating educational content (text) with relevant diagrams or illustrations (image).
Search Engines Optimization:
This Model could revolutionize image-based search engines by improving the accuracy of search results, pairing text queries with visual data to provide more relevant results.
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