Image-to-Text
PyTorch
Safetensors
PEFT
English
remote-sensing
satellite-imagery
earth-observation
change-detection
visual-grounding
image-captioning
visual-question-answering
optical-sar-fusion
sar
multimodal
lora
Instructions to use thundercode/SatQuery with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thundercode/SatQuery with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 12,336 Bytes
617fceb baf857b 617fceb baf857b 617fceb d08aa24 4af4c41 baf857b 4af4c41 baf857b 4af4c41 baf857b 4af4c41 baf857b 4af4c41 baf857b 4af4c41 baf857b 4af4c41 baf857b 4af4c41 baf857b 4af4c41 617fceb d08aa24 4af4c41 baf857b 617fceb 4af4c41 617fceb d08aa24 baf857b 617fceb baf857b d08aa24 4af4c41 617fceb baf857b d08aa24 baf857b d08aa24 baf857b 617fceb 4af4c41 baf857b 4af4c41 617fceb 4af4c41 baf857b 4af4c41 617fceb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 | # Release Manifest
**Repository:** `Anish-lab-blip/SatQuery-AI` (public)
**Generated:** 2026-09-25T23:09:39+00:00
**Generator:** `release/tools/generate_release_manifest.py` (computed from disk, never typed)
**Files:** 52 · **Total size:** 9,320,442 bytes (9102.0 KiB)
Every file in this release, with its size and sha256. Verify a checkout with:
```bash
# for each row: echo '<sha256> <path>' | sha256sum -c -
```
| # | Path | Bytes | sha256 |
|---|---|---|---|
| 1 | `HF_RELEASE_VERIFICATION.md` | 6,443 | `1d87487c2e9db5fb86781076c5061e2090077dbe90f8728f848eab0c615cf43e` |
| 2 | `MODEL_CARD.md` | 57,372 | `f2ab54a69886eecce8f55c1969715d03082133b939745dba71fd4896d8e17d2b` |
| 3 | `README.md` | 90,925 | `a4e0f99f215bb1daf8533593ad049a7f4c4458e52d4b3807c7c5abe8fc2e1a17` |
| 4 | `docs/BENCHMARKS.md` | 55,999 | `97cfe327793443f60c98e6948c1080a4fecab0cf721252f119deb20cc6736c09` |
| 5 | `docs/CHANGELOG.md` | 36,900 | `dd11f308b539d5e422960168ae3a1fef41e38b83a18a5ae34f9efc169e589d4f` |
| 6 | `docs/DATASETS.md` | 67,723 | `1aa5dc9715be4c94eb357d1066c79a6cc5d4c59ae4d587f249e3f1e66c1f628f` |
| 7 | `docs/DATA_PIPELINE.md` | 66,285 | `24a543fd4ac270d0d58976dff1ab247610c4be7698a15f9380dbdf27c0f92c8b` |
| 8 | `docs/DEPLOYMENT.md` | 45,966 | `df1264b5da664e909dbc7553ac9992721b9b2a9d7f931e81e0064304bbb038fe` |
| 9 | `docs/DEVELOPMENT.md` | 69,335 | `313622536676062725a1c5eb96143bd675fd181fe0d258d6dce636f9e8689f22` |
| 10 | `docs/EVALUATION.md` | 111,672 | `f35020b7a051409f1f53b7a1464eaa87252dd1dee6ea5bc378492e396063b48a` |
| 11 | `docs/FRONTEND.md` | 73,886 | `fcb81e084c04e0bcf814d6edcc8d797cc3ad29c709bd565c053586a0d30c6d68` |
| 12 | `docs/GEOSPATIAL.md` | 92,888 | `ff2753fa10b5db4971ae949c828b7ecb5909b8ad9ed6bed287864ab23d7f0d6c` |
| 13 | `docs/GLOSSARY.md` | 40,998 | `81f1a86d721e6517893bb56e5408b4315dd38a6b214e0f79f840b5ea9f8fc754` |
| 14 | `docs/LIMITATIONS.md` | 40,805 | `1205aab110bc0f34140d314ea6c2e723f37c973313d86339f8f7275a2bbed170` |
| 15 | `docs/MASTER_ARCHITECTURE_PLAN.md` | 65,311 | `d820d306c3b5e9d18e9d704d3cb4be5b4ec476e0524f690d456f0fac6e5bb49b` |
| 16 | `docs/MODELS.md` | 103,145 | `5a3b166035a2ee9ea53f5aa3a2f751045494562181bba8f8a85f7babba063d6f` |
| 17 | `docs/OPERATIONS.md` | 62,188 | `c14b3d9c66b8627c84af83723b4811f4f729df53e339434dbd912e17264c1c56` |
| 18 | `docs/PERFORMANCE.md` | 52,946 | `5c079ac08b7dc765af82a3dbf95e067b8797c8f9a30d23df9977252087c7fdee` |
| 19 | `docs/REPRODUCIBILITY.md` | 65,120 | `7e3cdcc57e56e5a99a1095df326cd65253ed873d80020b6095318f336a2ec726` |
| 20 | `docs/RESEARCH_NOTES.md` | 41,248 | `321226af9aaa903135730ea7a8a4e18a8d1999bdf30ff67b19417e34ab453651` |
| 21 | `docs/SECURITY.md` | 114,322 | `191446f458f08dc57e01824fff143edba741f4590b1d0eb85ea10f63798b3b40` |
| 22 | `docs/SERVING.md` | 75,757 | `92186b7b247647adf18229a4f6f97b6c36f82fb5cc931a7a0c6b76e0d329bed5` |
| 23 | `docs/TESTING.md` | 96,893 | `496b72038b66c5bad88f925e9036c789fed0733e3d2b199b243a2314f4752072` |
| 24 | `docs/TRAINING.md` | 90,697 | `7575748b37006b6353f511059ddf7c29cd210d84b47ec702b10eefc7297453f1` |
| 25 | `docs/architecture/01-system-overview.md` | 8,367 | `01b5a88b0bc77c1d8ea5439a70ab2fbbc55ce56840415f22d66af412f0bc9492` |
| 26 | `docs/architecture/02-deployment-topology.md` | 85,830 | `f2448816c7f9b5c2995ae32c99052249c908be17a3c22b12393f13dfe20effde` |
| 27 | `docs/architecture/03-request-lifecycle.md` | 130,166 | `be9edb87d8d86f923d13bbf15989af0f5b71d43be70b43dce8f4f8349eb37f6a` |
| 28 | `docs/architecture/04-router.md` | 262,643 | `556aba832e43c145b5f6e10188d9e4f65148adff59a9d69a6b6cb6a63f14efb4` |
| 29 | `docs/architecture/05-specialists.md` | 252,171 | `2966131b2adcbe7e07e0126508dff8d5c4eaa898c750b64e30fd44effe33b1b4` |
| 30 | `docs/architecture/06-evidence-and-confidence.md` | 108,035 | `98967c06328647f77c4e2d192a7056403e571b6b0e5a7a532a265ac6cc1d2779` |
| 31 | `docs/architecture/07-configuration-freeze.md` | 106,014 | `c8bbedee86859ffa7942d48d6d46adf493112122314245820ace7dd7bc56b970` |
| 32 | `docs/architecture/08-api-contract.md` | 127,332 | `f36dbb5d8d4f481cdbe46bf289915100ce3f5a36ecdbee1a5a0abb3a6391bffc` |
| 33 | `docs/architecture/09-frontend.md` | 78,258 | `a7343a07bc962f953764ddf818b730fad9303a3377f2c3cea0593a34e0dc78ae` |
| 34 | `docs/architecture/10-observability-and-ops.md` | 104,626 | `2df09eaab10c5b05b98d4909e439f74e1378022ab77c86c192526464cb686197` |
| 35 | `docs/architecture/README.md` | 7,610 | `b366886a648de3244174bf3c8a1a798d8c3b41af6f842d345d61f3149e97b0ec` |
| 36 | `models/checksums.sha256` | 642 | `f177e6fbc807868141378a75f36ca07cb01a8f859d9f80f1935fbf396ddf5380` |
| 37 | `models/manifest.json` | 4,458 | `ae1f55cf906095e089c769efb774a8461dc20b7076752e7fbae1091255f38eb0` |
| 38 | `screenshots/analyze-caption.png` | 890,381 | `428abb8edff78812f2e1cfb23965f00572e89d741f6fd56bf6c5f3d4d500293f` |
| 39 | `screenshots/analyze-change-vqa.png` | 694,618 | `0ddb4e6043443119db98ad4a70c637aacb27ec2404959f111bbe58c80c009e47` |
| 40 | `screenshots/analyze-change.png` | 445,200 | `a833e4e975c70659769f499525b6182a0bfb17f1fad3d213e9f303954a9ada87` |
| 41 | `screenshots/analyze-grounding-buildings.png` | 1,036,080 | `9714f51020b224271f22a3be44fedb94f7c3b532cca68ba32179debb7edcb604` |
| 42 | `screenshots/analyze-grounding-new-airport.png` | 1,042,892 | `5d5af7d23c9f8c1f3724cb7775f1873f199442d1afbfa3726a43495780052555` |
| 43 | `screenshots/analyze-grounding.png` | 1,035,183 | `b3199b55ea819d4955fcc713311c8fcb475f069aa99966e8fd577f21a16d184b` |
| 44 | `screenshots/analyze-optical-sar.png` | 131,330 | `6006c8b35217904bfe1042137c22de4d8765bc57b1efb418a131df9ce8477b94` |
| 45 | `screenshots/analyze-vqa.png` | 1,104,701 | `7ee1d95fa1fb29fce86cf4a3545a8fa8811dbe4c18af3acc7816838b1412ad62` |
| 46 | `tools/build_archive.py` | 8,351 | `73574bb0ec85d5f7505b51661021f844dfd43cd13fafc802f75aa3835dd6a1ae` |
| 47 | `tools/generate_model_manifest.py` | 6,868 | `f445a43c888a30fcd868d810f1cacf8e682e8ed331755c661de2c29fb8d59550` |
| 48 | `tools/generate_release_manifest.py` | 4,100 | `9facdcd4a3a5d23adbaccf34c4c7a89d661e1bed47e7da5dc6977181a8ac5884` |
| 49 | `tools/hf_verify.py` | 3,878 | `e6e59312bb9d20e103d7bd57b1924cc6fae0a4d1a552a2dd2fdbcce80885e86e` |
| 50 | `tools/readme_metrics_report.txt` | 4,027 | `25108a07f671b8a33e5c312a81ce9d18e7a9c06b4955fb137a0f62e20c5bb2dc` |
| 51 | `tools/verify_archive.py` | 4,946 | `babb44dbb60497172a70d0b3c4abc26520bd0e37ef06c215e3f016f0d25a1abf` |
| 52 | `tools/verify_readme_metrics.py` | 6,911 | `0ce1273aa5f847a56a38a4ca6601f50648d19cc1637394509ce5a9f1309ea388` |
## Machine-readable listing
```
1d87487c2e9db5fb86781076c5061e2090077dbe90f8728f848eab0c615cf43e HF_RELEASE_VERIFICATION.md
f2ab54a69886eecce8f55c1969715d03082133b939745dba71fd4896d8e17d2b MODEL_CARD.md
a4e0f99f215bb1daf8533593ad049a7f4c4458e52d4b3807c7c5abe8fc2e1a17 README.md
97cfe327793443f60c98e6948c1080a4fecab0cf721252f119deb20cc6736c09 docs/BENCHMARKS.md
dd11f308b539d5e422960168ae3a1fef41e38b83a18a5ae34f9efc169e589d4f docs/CHANGELOG.md
1aa5dc9715be4c94eb357d1066c79a6cc5d4c59ae4d587f249e3f1e66c1f628f docs/DATASETS.md
24a543fd4ac270d0d58976dff1ab247610c4be7698a15f9380dbdf27c0f92c8b docs/DATA_PIPELINE.md
df1264b5da664e909dbc7553ac9992721b9b2a9d7f931e81e0064304bbb038fe docs/DEPLOYMENT.md
313622536676062725a1c5eb96143bd675fd181fe0d258d6dce636f9e8689f22 docs/DEVELOPMENT.md
f35020b7a051409f1f53b7a1464eaa87252dd1dee6ea5bc378492e396063b48a docs/EVALUATION.md
fcb81e084c04e0bcf814d6edcc8d797cc3ad29c709bd565c053586a0d30c6d68 docs/FRONTEND.md
ff2753fa10b5db4971ae949c828b7ecb5909b8ad9ed6bed287864ab23d7f0d6c docs/GEOSPATIAL.md
81f1a86d721e6517893bb56e5408b4315dd38a6b214e0f79f840b5ea9f8fc754 docs/GLOSSARY.md
1205aab110bc0f34140d314ea6c2e723f37c973313d86339f8f7275a2bbed170 docs/LIMITATIONS.md
d820d306c3b5e9d18e9d704d3cb4be5b4ec476e0524f690d456f0fac6e5bb49b docs/MASTER_ARCHITECTURE_PLAN.md
5a3b166035a2ee9ea53f5aa3a2f751045494562181bba8f8a85f7babba063d6f docs/MODELS.md
c14b3d9c66b8627c84af83723b4811f4f729df53e339434dbd912e17264c1c56 docs/OPERATIONS.md
5c079ac08b7dc765af82a3dbf95e067b8797c8f9a30d23df9977252087c7fdee docs/PERFORMANCE.md
7e3cdcc57e56e5a99a1095df326cd65253ed873d80020b6095318f336a2ec726 docs/REPRODUCIBILITY.md
321226af9aaa903135730ea7a8a4e18a8d1999bdf30ff67b19417e34ab453651 docs/RESEARCH_NOTES.md
191446f458f08dc57e01824fff143edba741f4590b1d0eb85ea10f63798b3b40 docs/SECURITY.md
92186b7b247647adf18229a4f6f97b6c36f82fb5cc931a7a0c6b76e0d329bed5 docs/SERVING.md
496b72038b66c5bad88f925e9036c789fed0733e3d2b199b243a2314f4752072 docs/TESTING.md
7575748b37006b6353f511059ddf7c29cd210d84b47ec702b10eefc7297453f1 docs/TRAINING.md
01b5a88b0bc77c1d8ea5439a70ab2fbbc55ce56840415f22d66af412f0bc9492 docs/architecture/01-system-overview.md
f2448816c7f9b5c2995ae32c99052249c908be17a3c22b12393f13dfe20effde docs/architecture/02-deployment-topology.md
be9edb87d8d86f923d13bbf15989af0f5b71d43be70b43dce8f4f8349eb37f6a docs/architecture/03-request-lifecycle.md
556aba832e43c145b5f6e10188d9e4f65148adff59a9d69a6b6cb6a63f14efb4 docs/architecture/04-router.md
2966131b2adcbe7e07e0126508dff8d5c4eaa898c750b64e30fd44effe33b1b4 docs/architecture/05-specialists.md
98967c06328647f77c4e2d192a7056403e571b6b0e5a7a532a265ac6cc1d2779 docs/architecture/06-evidence-and-confidence.md
c8bbedee86859ffa7942d48d6d46adf493112122314245820ace7dd7bc56b970 docs/architecture/07-configuration-freeze.md
f36dbb5d8d4f481cdbe46bf289915100ce3f5a36ecdbee1a5a0abb3a6391bffc docs/architecture/08-api-contract.md
a7343a07bc962f953764ddf818b730fad9303a3377f2c3cea0593a34e0dc78ae docs/architecture/09-frontend.md
2df09eaab10c5b05b98d4909e439f74e1378022ab77c86c192526464cb686197 docs/architecture/10-observability-and-ops.md
b366886a648de3244174bf3c8a1a798d8c3b41af6f842d345d61f3149e97b0ec docs/architecture/README.md
f177e6fbc807868141378a75f36ca07cb01a8f859d9f80f1935fbf396ddf5380 models/checksums.sha256
ae1f55cf906095e089c769efb774a8461dc20b7076752e7fbae1091255f38eb0 models/manifest.json
428abb8edff78812f2e1cfb23965f00572e89d741f6fd56bf6c5f3d4d500293f screenshots/analyze-caption.png
0ddb4e6043443119db98ad4a70c637aacb27ec2404959f111bbe58c80c009e47 screenshots/analyze-change-vqa.png
a833e4e975c70659769f499525b6182a0bfb17f1fad3d213e9f303954a9ada87 screenshots/analyze-change.png
9714f51020b224271f22a3be44fedb94f7c3b532cca68ba32179debb7edcb604 screenshots/analyze-grounding-buildings.png
5d5af7d23c9f8c1f3724cb7775f1873f199442d1afbfa3726a43495780052555 screenshots/analyze-grounding-new-airport.png
b3199b55ea819d4955fcc713311c8fcb475f069aa99966e8fd577f21a16d184b screenshots/analyze-grounding.png
6006c8b35217904bfe1042137c22de4d8765bc57b1efb418a131df9ce8477b94 screenshots/analyze-optical-sar.png
7ee1d95fa1fb29fce86cf4a3545a8fa8811dbe4c18af3acc7816838b1412ad62 screenshots/analyze-vqa.png
73574bb0ec85d5f7505b51661021f844dfd43cd13fafc802f75aa3835dd6a1ae tools/build_archive.py
f445a43c888a30fcd868d810f1cacf8e682e8ed331755c661de2c29fb8d59550 tools/generate_model_manifest.py
9facdcd4a3a5d23adbaccf34c4c7a89d661e1bed47e7da5dc6977181a8ac5884 tools/generate_release_manifest.py
e6e59312bb9d20e103d7bd57b1924cc6fae0a4d1a552a2dd2fdbcce80885e86e tools/hf_verify.py
25108a07f671b8a33e5c312a81ce9d18e7a9c06b4955fb137a0f62e20c5bb2dc tools/readme_metrics_report.txt
babb44dbb60497172a70d0b3c4abc26520bd0e37ef06c215e3f016f0d25a1abf tools/verify_archive.py
0ce1273aa5f847a56a38a4ca6601f50648d19cc1637394509ce5a9f1309ea388 tools/verify_readme_metrics.py
```
## Contents summary
| Area | What it is |
|---|---|
| `README.md` | the repository front page |
| `MODEL_CARD.md` | model card for the six trained artifacts |
| `docs/` | the research + engineering documentation set |
| `docs/architecture/` | the deep architecture reference (multi-part) |
| `models/manifest.json` | generated manifest of the six trained artifacts |
| `models/checksums.sha256` | generated checksums for the six trained artifacts |
| `screenshots/` | real live-run captures |
## What this release deliberately does NOT contain
- **Backbone weights.** They are fetched from the Hugging Face Hub, pinned by revision.
- **Secrets.** No tokens, keys, or environment files.
- **The private deployment repositories.** Their sources are not published here.
- **Datasets.** Acquisition procedures are documented; the data is not redistributed.
- **A licence file.** None has been selected yet — this is an OPEN item.
|