Upload 6 files

.gitattributes

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+train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- en
+task_categories:
+- question-answering
+task_ids:
+- multiple-choice-qa
+pretty_name: GeneralScience-MLLM-22K
+size_categories:
+- 10K<n<100K
+tags:
+- science
+- multiple-choice-qa
+- multimodal
+- image-text
+- education
+- jsonl
+license: other
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: train.jsonl
+  - split: test
+    path: test.jsonl
+---
+
+# GeneralScience-MLLM-22K
+
+## Dataset Summary
+
+GeneralScience-MLLM-22K is a unified general-science multiple-choice QA collection built from local snapshots of SciQ, AI2 ARC, and ScienceQA. It follows the same release style as a subject-specific MLLM dataset: every sample is stored as one JSONL record, text-only and image-text examples share one schema, and ScienceQA images are exported as standalone files referenced by relative paths.
+
+The release contains **22,661** examples:
+
+- `train.jsonl`: 17,880 examples
+- `test.jsonl`: 4,781 held-out examples
+- `images/scienceqa/`: 351 exported ScienceQA images
+
+The upstream `test` splits are kept as held-out test data. Upstream `train` and `validation` splits are merged into `train.jsonl`.
+
+## Data Sources
+
+| Source | Subset | Count | Modality | License note |
+| --- | --- | ---: | --- | --- |
+| `allenai/sciq` | `null` | 13,679 | text | CC BY-NC 3.0, from local HF dataset card |
+| `allenai/ai2_arc` | `ARC-Challenge` | 2,581 | text | CC BY-SA 4.0, from local HF dataset card |
+| `allenai/ai2_arc` | `ARC-Easy` | 5,180 | text | CC BY-SA 4.0, from local HF dataset card |
+| `derek-thomas/ScienceQA` | `null` | 1,221 | text / image-text | License metadata was not included in the local snapshot; verify upstream before public redistribution |
+
+OpenBookQA exists in the local workspace but is **not included** in this main release because its license was not confirmed in the local snapshot.
+
+## File Structure
+
+```text
+general_science_release/
+  README.md
+  general_science_card.md
+  stats.json
+  train.jsonl
+  test.jsonl
+  images/
+    scienceqa/
+      *.png
+  scripts/
+    build_general_science_release.py
+    validate_general_science_release.py
+```
+
+## Data Format
+
+Each line in `train.jsonl` and `test.jsonl` is one JSON object:
+
+```json
+{
+  "id": "scienceqa-train-09049",
+  "dataset": "derek-thomas/ScienceQA",
+  "subset": null,
+  "split": "train",
+  "task_type": "multiple_choice_science_qa",
+  "modality": "image_text",
+  "question": "What is the probability that a rainbow trout produced by this cross will be homozygous dominant for the body color gene?",
+  "image": {
+    "path": "images/scienceqa/scienceqa-train-09049.png",
+    "mime_type": "image/png"
+  },
+  "choices": [
+    {"label": "A", "text": "1/4"},
+    {"label": "B", "text": "2/4"},
+    {"label": "C", "text": "3/4"},
+    {"label": "D", "text": "0/4"},
+    {"label": "E", "text": "4/4"}
+  ],
+  "answer_label": "D",
+  "answer_text": "0/4",
+  "support": "...",
+  "source_meta": {
+    "source_file": "scienceqa_hf/data/train-00000-of-00001-1028f23e353fbe3e.parquet",
+    "source_split": "train",
+    "source_index": 9049
+  }
+}
+```
+
+For text-only examples, `image` is `null` and `modality` is `text`.
+
+## Field Meaning
+
+- `id`: unique example ID in this release.
+- `dataset`: upstream dataset name.
+- `subset`: upstream subset/config name, or `null`.
+- `split`: release split, either `train` or `test`.
+- `task_type`: fixed as `multiple_choice_science_qa`.
+- `modality`: `text` or `image_text`.
+- `question`: question text.
+- `image`: relative image path and MIME type for image-text examples; otherwise `null`.
+- `choices`: regenerated multiple-choice options, labeled from `A`.
+- `answer_label`: correct answer label after option shuffling.
+- `answer_text`: correct answer text.
+- `support`: explanation or supporting context when available.
+- `source_meta`: source file, original split/index, original answer metadata, and license notes.
+
+## Statistics
+
+Token statistics use `regex_approx_v1` because `tiktoken` was not installed in the local `memory` environment during construction.
+
+| Split | Examples | Image examples | Text examples | Avg input tokens | Avg support tokens | Avg full record tokens |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: |
+| train | 17,880 | 281 | 17,599 | 33.83 | 73.63 | 394.80 |
+| test | 4,781 | 70 | 4,711 | 44.56 | 33.46 | 386.07 |
+| overall | 22,661 | 351 | 22,310 | 36.09 | 65.15 | 392.96 |
+
+Modality distribution:
+
+| Modality | Count |
+| --- | ---: |
+| text | 22,310 |
+| image_text | 351 |
+
+## Construction Method
+
+1. Read local parquet files only; no dataset is re-downloaded.
+2. Convert every valid example into the unified JSONL schema.
+3. Merge upstream `train` and `validation` into release `train`.
+4. Keep upstream `test` as release `test`.
+5. Export ScienceQA image bytes to `images/scienceqa/` and store relative paths in JSONL.
+6. Deterministically shuffle choices with `seed=42`.
+7. Remove normalized duplicates within split.
+8. Remove train examples whose normalized question+choices+answer key overlaps with held-out test.
+
+Deduplication summary:
+
+```json
+{
+  "train_duplicates_removed": 9,
+  "test_duplicates_removed": 0,
+  "train_removed_for_test_overlap": 7,
+  "train_test_overlap_after_filter": 0
+}
+```
+
+## How to Load
+
+```python
+import json
+from pathlib import Path
+
+root = Path("general_science_release")
+
+with (root / "train.jsonl").open(encoding="utf-8") as f:
+    first = json.loads(next(f))
+
+print(first["question"])
+print(first["choices"])
+
+if first["image"] is not None:
+    image_path = root / first["image"]["path"]
+    print(image_path)
+```
+
+For model evaluation, use `question`, `image`, and `choices` as input. Do not feed `support` unless the task explicitly allows explanation or retrieval context, because `support` may reveal the answer.
+
+## Validation
+
+The release was checked with:
+
+```bash
+conda run -n memory python scripts/validate_general_science_release.py
+```
+
+Validation result:
+
+```text
+train=17880
+test=4781
+total=22661
+image_examples=351
+validation=ok
+```
+
+## License
+
+This release combines multiple upstream datasets and should be redistributed only under terms compatible with all included sources.
+
+- SciQ: CC BY-NC 3.0 according to the local Hugging Face dataset card.
+- AI2 ARC: CC BY-SA 4.0 according to the local Hugging Face dataset card.
+- ScienceQA: license metadata was not available in the local snapshot used here; verify the upstream dataset license before public HF/ModelScope upload.
+
+Because the combined release includes non-commercial and share-alike sources, downstream usage should be treated conservatively. Public upload should include the source attribution and license notes above.

UPLOAD.md

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+# Upload Guide
+
+This release is ready up to the pre-upload stage. The local package is:
+
+```text
+/home/ps/sjj/project/Memory/dataset/general/general_science_release.tar.gz
+```
+
+The folder to upload is:
+
+```text
+/home/ps/sjj/project/Memory/dataset/general/general_science_release
+```
+
+## 1. Pre-upload Check
+
+Run:
+
+```bash
+cd /home/ps/sjj/project/Memory/dataset/general/general_science_release
+conda run -n memory python scripts/validate_general_science_release.py
+```
+
+Expected result:
+
+```text
+validation=ok
+```
+
+## 2. Hugging Face Upload
+
+### Option A: Web Upload
+
+1. Create a new dataset repository on Hugging Face.
+2. Suggested repo name:
+
+```text
+gineven/GeneralScience-MLLM-22K
+```
+
+3. Upload the contents of `general_science_release/`.
+4. Keep the folder structure unchanged:
+
+```text
+README.md
+general_science_card.md
+stats.json
+train.jsonl
+test.jsonl
+images/scienceqa/*.png
+scripts/*.py
+```
+
+### Option B: CLI Upload
+
+Install or update the HF hub client if needed:
+
+```bash
+pip install -U huggingface_hub
+```
+
+Login:
+
+```bash
+hf auth login
+```
+
+Create the dataset repo:
+
+```bash
+# You already created this repository:
+# https://huggingface.co/datasets/gineven/GeneralScience-MLLM-22K
+```
+
+Upload the folder:
+
+```bash
+cd /home/ps/sjj/project/Memory/dataset/general
+hf upload gineven/GeneralScience-MLLM-22K general_science_release . \
+  --repo-type dataset \
+  --exclude "*/__pycache__/*" \
+  --exclude "*.pyc"
+```
+
+If your installed CLI uses the older command name, use:
+
+```bash
+huggingface-cli login
+# Repository already exists:
+# https://huggingface.co/datasets/gineven/GeneralScience-MLLM-22K
+```
+
+Then upload with Python API as shown below.
+
+### Option C: Python API Upload
+
+```python
+from huggingface_hub import HfApi
+
+api = HfApi()
+repo_id = "gineven/GeneralScience-MLLM-22K"
+
+api.create_repo(repo_id=repo_id, repo_type="dataset", exist_ok=True)
+api.upload_folder(
+    repo_id=repo_id,
+    repo_type="dataset",
+    folder_path="/home/ps/sjj/project/Memory/dataset/general/general_science_release",
+    path_in_repo=".",
+    ignore_patterns=["*/__pycache__/*", "*.pyc"],
+)
+```
+
+After upload, the expected download link is:
+
+```text
+https://huggingface.co/datasets/gineven/GeneralScience-MLLM-22K
+```
+
+## 3. ModelScope Upload
+
+ModelScope upload is similar in spirit: create a dataset repository, then upload the same folder contents. Keep `README.md`, `train.jsonl`, `test.jsonl`, `stats.json`, and `images/scienceqa/` at the repository root.
+
+If using `modelscope` CLI/API, first make sure your account is logged in and then upload the `general_science_release/` directory as a dataset repository.
+
+## 4. Netdisk Fallback
+
+If HF/ModelScope credentials are not available, upload:
+
+```text
+general_science_release.tar.gz
+```
+
+Then share the netdisk URL together with:
+
+```text
+general_science_release/general_science_card.md
+general_science_release/stats.json
+```
+
+## 5. Important License Check
+
+Before public upload, manually verify the upstream ScienceQA license because the local snapshot used for this build does not include license metadata. The current `README.md` marks the combined license as `other` and records the missing ScienceQA license note.

general_science_card.md

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+# General Science QA Release
+
+## Summary
+
+This release consolidates local science QA snapshots into a unified JSONL format for text and image-text multiple-choice science QA.
+It is built from local parquet files only and stops before any public upload.
+
+## Output Files
+
+- `train.jsonl`
+- `test.jsonl`
+- `stats.json`
+- `images/scienceqa/`
+- `general_science_card.md`
+- `README.md`
+
+## Sources
+
+| Dataset | Subset | License | License source | URL |
+| --- | --- | --- | --- | --- |
+| allenai/sciq | `null` | CC BY-NC 3.0 | local Hugging Face dataset card: sciq/README.md | https://huggingface.co/datasets/allenai/sciq |
+| allenai/ai2_arc | ARC-Challenge, ARC-Easy | CC BY-SA 4.0 | local Hugging Face dataset card: ai2_arc/README.md | https://huggingface.co/datasets/allenai/ai2_arc |
+| derek-thomas/ScienceQA | `null` | TBD: not available in local snapshot | local parquet snapshot does not include README/license metadata; verify upstream before public upload | https://huggingface.co/datasets/derek-thomas/ScienceQA |
+
+OpenBookQA is present locally but is not included in this main release because its license is not confirmed in the local snapshot. It can be added later as an internal/optional extension after license confirmation.
+
+## Split Construction
+
+- Upstream `train` and `validation` splits are merged into `train.jsonl`.
+- Upstream `test` splits are kept as the held-out `test.jsonl`.
+- Train/test leakage is checked using normalized question, choices, and answer text.
+- If a normalized duplicate appears in held-out test, the matching train example is removed.
+
+## Schema
+
+```json
+{
+  "id": "string",
+  "dataset": "string",
+  "subset": "string or null",
+  "split": "train or test",
+  "task_type": "multiple_choice_science_qa",
+  "modality": "text or image_text",
+  "question": "string",
+  "image": null,
+  "choices": [
+    {"label": "A", "text": "string"}
+  ],
+  "answer_label": "string",
+  "answer_text": "string",
+  "support": "string or null",
+  "source_meta": {}
+}
+```
+
+For ScienceQA image examples, `image` is:
+
+```json
+{"path": "images/scienceqa/<id>.png", "mime_type": "image/png"}
+```
+
+## Counts and Token Statistics
+
+Tokenizer: `regex_approx_v1`.
+
+| Split | Examples | Image examples | Text examples | Avg input tokens | Avg support tokens | Avg full record tokens |
+| --- | --- | --- | --- | --- | --- | --- |
+| train | 17880 | 281 | 17599 | 33.83 | 73.63 | 394.8 |
+| test | 4781 | 70 | 4711 | 44.56 | 33.46 | 386.07 |
+| overall | 22661 | 351 | 22310 | 36.09 | 65.15 | 392.96 |
+
+## Counts by Dataset
+
+| Dataset | Subset | Examples | Image examples | Avg input tokens | Avg support tokens |
+| --- | --- | --- | --- | --- | --- |
+| allenai/ai2_arc | ARC-Challenge | 2581 | 0 | 55.2 | 0.0 |
+| allenai/ai2_arc | ARC-Easy | 5180 | 0 | 46.19 | 0.0 |
+| allenai/sciq | None | 13679 | 0 | 28.46 | 78.92 |
+| derek-thomas/ScienceQA | None | 1221 | 351 | 38.32 | 325.07 |
+
+## Modality Distribution
+
+| Modality | Count |
+| --- | --- |
+| image_text | 351 |
+| text | 22310 |
+
+## Deduplication
+
+```json
+{
+  "train_duplicates_removed": 9,
+  "test_duplicates_removed": 0,
+  "train_removed_for_test_overlap": 7,
+  "train_test_overlap_after_filter": 0
+}
+```
+
+## Construction Notes
+
+- SciQ: combines `distractor1`, `distractor2`, `distractor3`, and `correct_answer`, then deterministically shuffles choices.
+- AI2 ARC: uses both `ARC-Challenge` and `ARC-Easy`; finds the answer text from `answerKey`, then deterministically shuffles choices.
+- ScienceQA: keeps `subject == "natural science"` examples with at least four choices and a valid answer index. Images embedded as parquet bytes are exported to `images/scienceqa/`.
+- Choices with more than four options are retained; labels are regenerated from `A`.
+
+## License Notes
+
+This release combines multiple upstream datasets. Downstream redistribution must satisfy all upstream licenses.
+ScienceQA license metadata was not present in the local snapshot available to this build; verify the upstream license before public HF/ModelScope upload.
+
+## Recommended Evaluation Input
+
+For model evaluation, use `question`, `image`, and `choices`.
+Do not feed `support` unless the task explicitly allows explanations or retrieval context, because `support` may contain answer-revealing information.

stats.json

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+{
+  "name": "general_science_release",
+  "version": "v0.1-local",
+  "generated_at_utc": "2026-07-15T16:51:16.510238+00:00",
+  "seed": 42,
+  "tokenizer": {
+    "name": "regex_approx_v1",
+    "note": "Token counts are computed over question+choices(+image placeholder), support, and serialized full JSON record."
+  },
+  "splits": {
+    "train": {
+      "num_examples": 17880,
+      "input_tokens": 604879,
+      "support_tokens": 1316504,
+      "full_record_tokens": 7059099,
+      "image_examples": 281,
+      "text_examples": 17599,
+      "avg_input_tokens": 33.83,
+      "avg_support_tokens": 73.63,
+      "avg_full_record_tokens": 394.8
+    },
+    "test": {
+      "num_examples": 4781,
+      "input_tokens": 213028,
+      "support_tokens": 159956,
+      "full_record_tokens": 1845777,
+      "image_examples": 70,
+      "text_examples": 4711,
+      "avg_input_tokens": 44.56,
+      "avg_support_tokens": 33.46,
+      "avg_full_record_tokens": 386.07
+    },
+    "overall": {
+      "num_examples": 22661,
+      "input_tokens": 817907,
+      "support_tokens": 1476460,
+      "full_record_tokens": 8904876,
+      "image_examples": 351,
+      "text_examples": 22310,
+      "avg_input_tokens": 36.09,
+      "avg_support_tokens": 65.15,
+      "avg_full_record_tokens": 392.96
+    }
+  },
+  "by_dataset": {
+    "allenai/ai2_arc|ARC-Challenge": {
+      "num_examples": 2581,
+      "input_tokens": 142472,
+      "support_tokens": 0,
+      "full_record_tokens": 955225,
+      "image_examples": 0,
+      "text_examples": 2581,
+      "avg_input_tokens": 55.2,
+      "avg_support_tokens": 0.0,
+      "avg_full_record_tokens": 370.1
+    },
+    "allenai/ai2_arc|ARC-Easy": {
+      "num_examples": 5180,
+      "input_tokens": 239284,
+      "support_tokens": 0,
+      "full_record_tokens": 1862467,
+      "image_examples": 0,
+      "text_examples": 5180,
+      "avg_input_tokens": 46.19,
+      "avg_support_tokens": 0.0,
+      "avg_full_record_tokens": 359.55
+    },
+    "allenai/sciq|None": {
+      "num_examples": 13679,
+      "input_tokens": 389365,
+      "support_tokens": 1079550,
+      "full_record_tokens": 5190340,
+      "image_examples": 0,
+      "text_examples": 13679,
+      "avg_input_tokens": 28.46,
+      "avg_support_tokens": 78.92,
+      "avg_full_record_tokens": 379.44
+    },
+    "derek-thomas/ScienceQA|None": {
+      "num_examples": 1221,
+      "input_tokens": 46786,
+      "support_tokens": 396910,
+      "full_record_tokens": 896844,
+      "image_examples": 351,
+      "text_examples": 870,
+      "avg_input_tokens": 38.32,
+      "avg_support_tokens": 325.07,
+      "avg_full_record_tokens": 734.52
+    }
+  },
+  "by_modality": {
+    "text": 22310,
+    "image_text": 351
+  },
+  "source_files": {
+    "allenai/sciq|None|train": {
+      "display_name": "SciQ",
+      "dataset": "allenai/sciq",
+      "subset": null,
+      "source_split": "train",
+      "final_split": "train",
+      "source_file": "sciq/data/train-00000-of-00001.parquet",
+      "raw_rows": 11679,
+      "converted": 11679,
+      "skipped": 0
+    },
+    "allenai/sciq|None|validation": {
+      "display_name": "SciQ",
+      "dataset": "allenai/sciq",
+      "subset": null,
+      "source_split": "validation",
+      "final_split": "train",
+      "source_file": "sciq/data/validation-00000-of-00001.parquet",
+      "raw_rows": 1000,
+      "converted": 1000,
+      "skipped": 0
+    },
+    "allenai/sciq|None|test": {
+      "display_name": "SciQ",
+      "dataset": "allenai/sciq",
+      "subset": null,
+      "source_split": "test",
+      "final_split": "test",
+      "source_file": "sciq/data/test-00000-of-00001.parquet",
+      "raw_rows": 1000,
+      "converted": 1000,
+      "skipped": 0
+    },
+    "allenai/ai2_arc|ARC-Challenge|train": {
+      "display_name": "AI2 ARC-Challenge",
+      "dataset": "allenai/ai2_arc",
+      "subset": "ARC-Challenge",
+      "source_split": "train",
+      "final_split": "train",
+      "source_file": "ai2_arc/ARC-Challenge/train-00000-of-00001.parquet",
+      "raw_rows": 1119,
+      "converted": 1118,
+      "skipped": 1
+    },
+    "allenai/ai2_arc|ARC-Challenge|validation": {
+      "display_name": "AI2 ARC-Challenge",
+      "dataset": "allenai/ai2_arc",
+      "subset": "ARC-Challenge",
+      "source_split": "validation",
+      "final_split": "train",
+      "source_file": "ai2_arc/ARC-Challenge/validation-00000-of-00001.parquet",
+      "raw_rows": 299,
+      "converted": 296,
+      "skipped": 3
+    },
+    "allenai/ai2_arc|ARC-Challenge|test": {
+      "display_name": "AI2 ARC-Challenge",
+      "dataset": "allenai/ai2_arc",
+      "subset": "ARC-Challenge",
+      "source_split": "test",
+      "final_split": "test",
+      "source_file": "ai2_arc/ARC-Challenge/test-00000-of-00001.parquet",
+      "raw_rows": 1172,
+      "converted": 1168,
+      "skipped": 4
+    },
+    "allenai/ai2_arc|ARC-Easy|train": {
+      "display_name": "AI2 ARC-Easy",
+      "dataset": "allenai/ai2_arc",
+      "subset": "ARC-Easy",
+      "source_split": "train",
+      "final_split": "train",
+      "source_file": "ai2_arc/ARC-Easy/train-00000-of-00001.parquet",
+      "raw_rows": 2251,
+      "converted": 2245,
+      "skipped": 6
+    },
+    "allenai/ai2_arc|ARC-Easy|validation": {
+      "display_name": "AI2 ARC-Easy",
+      "dataset": "allenai/ai2_arc",
+      "subset": "ARC-Easy",
+      "source_split": "validation",
+      "final_split": "train",
+      "source_file": "ai2_arc/ARC-Easy/validation-00000-of-00001.parquet",
+      "raw_rows": 570,
+      "converted": 569,
+      "skipped": 1
+    },
+    "allenai/ai2_arc|ARC-Easy|test": {
+      "display_name": "AI2 ARC-Easy",
+      "dataset": "allenai/ai2_arc",
+      "subset": "ARC-Easy",
+      "source_split": "test",
+      "final_split": "test",
+      "source_file": "ai2_arc/ARC-Easy/test-00000-of-00001.parquet",
+      "raw_rows": 2376,
+      "converted": 2369,
+      "skipped": 7
+    },
+    "derek-thomas/ScienceQA|None|train": {
+      "display_name": "ScienceQA",
+      "dataset": "derek-thomas/ScienceQA",
+      "subset": null,
+      "source_split": "train",
+      "final_split": "train",
+      "source_file": "scienceqa_hf/data/train-00000-of-00001-1028f23e353fbe3e.parquet",
+      "raw_rows": 12726,
+      "converted": 721,
+      "skipped": 12005
+    },
+    "derek-thomas/ScienceQA|None|validation": {
+      "display_name": "ScienceQA",
+      "dataset": "derek-thomas/ScienceQA",
+      "subset": null,
+      "source_split": "validation",
+      "final_split": "train",
+      "source_file": "scienceqa_hf/data/validation-00000-of-00001-6c7328ff6c84284c.parquet",
+      "raw_rows": 4241,
+      "converted": 268,
+      "skipped": 3973
+    },
+    "derek-thomas/ScienceQA|None|test": {
+      "display_name": "ScienceQA",
+      "dataset": "derek-thomas/ScienceQA",
+      "subset": null,
+      "source_split": "test",
+      "final_split": "test",
+      "source_file": "scienceqa_hf/data/test-00000-of-00001-f0e719df791966ff.parquet",
+      "raw_rows": 4241,
+      "converted": 244,
+      "skipped": 3997
+    }
+  },
+  "deduplication": {
+    "train_duplicates_removed": 9,
+    "test_duplicates_removed": 0,
+    "train_removed_for_test_overlap": 7,
+    "train_test_overlap_after_filter": 0
+  },
+  "sources": {
+    "allenai/sciq": {
+      "license": "CC BY-NC 3.0",
+      "license_id": "cc-by-nc-3.0",
+      "license_source": "local Hugging Face dataset card: sciq/README.md",
+      "url": "https://huggingface.co/datasets/allenai/sciq"
+    },
+    "allenai/ai2_arc": {
+      "license": "CC BY-SA 4.0",
+      "license_id": "cc-by-sa-4.0",
+      "license_source": "local Hugging Face dataset card: ai2_arc/README.md",
+      "url": "https://huggingface.co/datasets/allenai/ai2_arc"
+    },
+    "derek-thomas/ScienceQA": {
+      "license": "TBD: not available in local snapshot",
+      "license_id": "unknown-local-snapshot",
+      "license_source": "local parquet snapshot does not include README/license metadata; verify upstream before public upload",
+      "url": "https://huggingface.co/datasets/derek-thomas/ScienceQA"
+    }
+  },
+  "outputs": {
+    "train": "train.jsonl",
+    "test": "test.jsonl",
+    "stats": "stats.json",
+    "card": "general_science_card.md",
+    "readme": "README.md",
+    "scienceqa_images": "images/scienceqa"
+  }
+}

train.jsonl

@@ -0,0 +1,3 @@
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+size 23153984