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Co-authored-by: Blake S <bsnelling@users.noreply.huggingface.co>

data_summary_card.md

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+# Data Summary for microsoft_llava-med-v1.5-mistral-7b 
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+ ## 1. General information 
+
+**1.0.1 Version of the Summary:** 1.0 
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+ 
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+**1.0.2 Last update:** 24-Nov-2025  
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+ 
+
+ ## 1.1 Model Developer Identification 
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+**1.1.1 Model Developer name and contact details:** Microsoft Corporation at One Microsoft Way, Redmond, WA 98052. Tel: 425-882-8080 
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+ 
+
+## 1.2 Model Identification 
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+**1.2.1 Versioned model name(s):** LLaVA-Med-v1.5-Mistral-7B 
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+ 
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+## 1.2.2 Model release date: 14-May-2024 
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+ 
+
+## 1.3 Overall training data size and characteristics 
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+### 1.3.1 Size of dataset and characteristics 
+
+**1.3.1.A Text training data size:** Less than 1 billion tokens 
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+ 
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+**1.3.1.B Text training data content:** Med builds upon [PMC-15 dataset,](https://https://arxiv.org/abs/2303.00915) which is a large-scale parallel image-text dataset for biomedical vision-language processing. It contains 15 million figure-caption pairs extracted from biomedical research articles in PubMed Central. 
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+ 
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+**1.3.1.C Image training data size:** Less than 1 billion tokens 
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+ 
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+**1.3.1.D Image training data content:** Biomedical figures and images extracted from PubMed Central research articles, including microscopy, radiography, histology, chest X-rays, CT and MRI scans, gross pathology images, and diverse figure-caption pairs 
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+ 
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+**1.3.1.E Audio training data size:** Not applicable 
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+ 
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+**1.3.1.F Audio training data content:** Not applicable 
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+ 
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+**1.3.1.G Video training data size:** Not applicable 
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+ 
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+**1.3.1.H Video training data content:** Not applicable 
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+ 
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+**1.3.1.I Other training data size:** Not applicable 
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+ 
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+**1.3.1.J Other training data content:** Not applicable 
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+ 
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+**1.3.2 Latest date of data acquisition/collection for model training:** 01-May-2024  
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+ 
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+**1.3.3 Is data collection ongoing to update the model with new data collection after deployment?** No 
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+ 
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+**1.3.4 Date the training dataset was first used to train the model:** 01-May-2024 
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+ 
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+**1.3.5 Rationale or purpose of data selection:** The dataset leverages PMC-15M, a broad-coverage biomedical figure-caption corpus, to align biomedical visual concepts and enable open-ended instruction-following. This supports research use by improving biomedical VQA and visual chat capabilities through curriculum learning using diverse, automatically generated instruction data 
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+ 
+
+## 2. List of data sources 
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+ ### 2.1 Publicly available datasets 
+
+**2.1.1 Have you used publicly available datasets to train the model?** Yes 
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+ 
+
+ ## 2.2 Private non-publicly available datasets obtained from third parties 
+
+ ### 2.2.1 Datasets commercially licensed by rights holders or their representatives 
+
+**2.2.1.A Have you concluded transactional commercial licensing agreement(s) with rights holder(s) or with their representatives?** Not applicable 
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+ 
+
+ ### 2.2.2 Private datasets obtained from other third-parties 
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+**2.2.2.A Have you obtained private datasets from third parties that are not licensed as described in Section 2.2.1, such as data obtained from providers of private databases, or data intermediaries?** No 
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+ 
+
+## 2.3 Personal Information 
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+**2.3.1 Was personal data used to train the model?** Microsoft follows all relevant laws and regulations pertaining to personal information 
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+ 
+
+## 2.4 Synthetic data 
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+**2.4.1 Was any synthetic AI-generated data used to train the model?** Yes 
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+ 
+
+## 3. Data processing aspects 
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+### 3.1 Respect of reservation of rights from text and data mining exception or limitation 
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+**3.1.1 Does this dataset include any data protected by copyright, trademark, or patent?** Microsoft follows all required regulations and laws for processing data protected by copyright, trademark, or patent 
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+ 
+
+## 3.2 Other information 
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+**3.2.1 Does the dataset include information about consumer groups without revealing individual consumer identities?**  Microsoft follows all required regulations and laws for protecting consumer identities 
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+ 
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+**3.2.2 Was the dataset cleaned or modified before model training?** Yes 
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+