Publish GenLLaVA dataset and provenance

README.md

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+---
+language:
+- en
+tags:
+- multimodal
+- instruction-tuning
+- genllava
+configs:
+- config_name: default
+  default: true
+  data_files:
+  - split: train
+    path: data/*/*.parquet
+- config_name: llava_text
+  data_files:
+  - split: train
+    path: data/llava_text/*.parquet
+- config_name: llava_understanding
+  data_files:
+  - split: train
+    path: data/llava_understanding/*.parquet
+- config_name: lvis
+  data_files:
+  - split: train
+    path: data/lvis/*.parquet
+- config_name: editing
+  data_files:
+  - split: train
+    path: data/editing/*.parquet
+- config_name: generation
+  data_files:
+  - split: train
+    path: data/generation/*.parquet
+- config_name: lrv
+  data_files:
+  - split: train
+    path: data/lrv/*.parquet
+- config_name: laion_gpt4v
+  data_files:
+  - split: train
+    path: data/laion_gpt4v/*.parquet
+- config_name: sharegpt4v
+  data_files:
+  - split: train
+    path: data/sharegpt4v/*.parquet
+- config_name: docvqa
+  data_files:
+  - split: train
+    path: data/docvqa/*.parquet
+- config_name: synthdog
+  data_files:
+  - split: train
+    path: data/synthdog/*.parquet
+- config_name: chartqa
+  data_files:
+  - split: train
+    path: data/chartqa/*.parquet
+- config_name: dvqa
+  data_files:
+  - split: train
+    path: data/dvqa/*.parquet
+- config_name: ai2d
+  data_files:
+  - split: train
+    path: data/ai2d/*.parquet
+---
+# Generative Visual Instruction Tuning
+
+Release of dataset for **Generative Visual Instruction Tuning**. 
+
+## Contents
+
+| Task | Rows |
+|---|---:|
+| text | 40,688 |
+| understanding | 1,221,051 |
+| editing | 200,000 |
+| generation | 558,120 |
+
+| Component | Packaged rows |
+|---|---:|
+| llava_text | 40,688 |
+| llava_understanding | 624,207 |
+| lvis | 213,690 |
+| editing | 200,000 |
+| generation | 558,120 |
+| lrv | 79,798 |
+| laion_gpt4v | 11,576 |
+| sharegpt4v | 102,025 |
+| docvqa | 39,461 |
+| synthdog | 65,000 |
+| chartqa | 22,881 |
+| dvqa | 50,000 |
+| ai2d | 12,413 |
+
+Only training data are packaged. 
+
+## Loading
+
+Load the complete mixture or one component:
+
+```python
+from datasets import load_dataset
+data = load_dataset("jefehern/genllava", "default", split="train", streaming=True)
+editing = load_dataset("jefehern/genllava", "editing", split="train", streaming=True)
+example = next(iter(editing))
+source_image = example["input_images"][0]
+edited_image = example["target_image"]
+```
+## Record schema and training use
+`task` is `text`, `understanding`, `generation`, or `editing`. `messages` contains role/content pairs. Understanding rows provide `input_images`; generation rows provide only `target_image`; editing rows provide one source image and a separate target. Text rows have neither.
+
+`<image>` identifies a supplied input image; `<image_output>` marks image supervision. These are semantic dataset markers.  This dataset preserves full released conversations and exact OCR labels; it does not apply the paper's 2,048-token text truncation or reproduce an unspecified task-token placement.
+
+## Recipe decisions and exclusions
+- The 40,688 text-only ShareGPT conversations were partitioned from LLaVA's 665,298 records and counted once.
+- All 558,128 released generation pairs and all 102,025 ShareGPT4V caption rows were considered. Duplicate or invalid records were removed and counts are reported above.
+- Editing selects 200K source rows, SynthDoG 65K, ChartQA 23K, and DVQA 50K by seed-7 BLAKE2b ranking. LRV selects 80K unique source QA records from the two upstream coordinate-free releases plus chart annotations. No rows are added back after quality exclusions or exact deduplication.
+- DocVQA uses its 39,463-question training split. AI2D uses 12,413 records whose 3,246 image IDs have zero overlap with the official test split's 814 image IDs. Validation/test questions are not added to reach the paper's rounded targets.
+- LAION has 12,356 released metadata rows. **11,576** images were recovered; **780** remain unavailable after mirror recovery and bounded URL retries.
+- Deduplication uses exact task/messages/input-image hashes/target-image hash. It retains different questions about the same image. Global duplicates and held-out image matches removed during packaging are listed in `provenance/package_exclusions.jsonl`.
+
+## Sources
+- [LLaVA generation / pretrain](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain)
+- [LLaVA instruction mixture, including ShareGPT](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K)
+- [LVIS-Instruct4V](https://huggingface.co/datasets/X2FD/LVIS-Instruct4V)
+- [InstructPix2Pix](https://huggingface.co/datasets/timbrooks/instructpix2pix-clip-filtered)
+- [LRV coordinate-free annotations and chart data](https://github.com/FuxiaoLiu/LRV-Instruction)
+- [LAION-GPT4V](https://huggingface.co/datasets/laion/gpt4v-dataset)
+- [ShareGPT4V](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V)
+- [DocVQA](https://huggingface.co/datasets/pixparse/docvqa-single-page-questions)
+- [SynthDoG English](https://huggingface.co/datasets/naver-clova-ix/synthdog-en)
+- [ChartQA](https://huggingface.co/datasets/HuggingFaceM4/ChartQA)
+- [DVQA](https://huggingface.co/datasets/vikhyatk/dvqa)
+- [AI2D subset and image assets](https://huggingface.co/datasets/Lin-Chen/Open-LLaVA-NeXT-mix1M)

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