Captioning Inceptionv3 Transformer
InceptionV3 + Transformer image captioning architecture.
Fuente del modelo
- Tipo
- Modelo
- Tamaño del archivo
- 216 MB
- Versión
- vRevision 59d93b4
- Actualizado
- 30 oct 2026
- Descargas
- 0
- Fuente
- Hugging Face
Descripción de la fuente
Image Captioning System — Dev Scaffold (v1.0.0)
InceptionV3 + Transformer image captioning architecture.
This release contains a deployment scaffold used for end-to-end system validation and infrastructure testing. It is intentionally published before the production training run so the full serving stack (FastAPI backend, Hugging Face Spaces container, Vercel frontend, GitHub Actions CI/CD) can be exercised end-to-end.
Purpose
- FastAPI inference serving
- Hugging Face Hub
snapshot_downloadintegration - Frontend / backend deployment validation
- CI/CD pipeline validation
- Production ML system architecture demonstration
Architecture
- Encoder: frozen InceptionV3 (ImageNet weights, 2048-dim features)
- Decoder: single Transformer decoder layer, d_model=512, 8 heads
- Vocab size: 52 tokens (scaffold) — production target is 15,000 (COCO)
- Max caption length: 40 tokens
⚠️ Current limitations
The decoder weights are bootstrap development artefacts generated by a synthetic 10-sentence corpus, not trained on the full COCO dataset. Caption outputs will be incoherent and limited to the 52-token scaffold vocabulary. The encoder is fully functional (real ImageNet weights); only the decoder is untrained.
Future revisions will replace these weights with a model trained on
MS COCO 2017 via scripts/train.py and configs/train/stabilized.yaml.
Files
| File | Size | SHA-256 |
|---|---|---|
model.h5 | 158 MB | bfe020d920aa2f3d019bf7b5b33904384057372e7c304a9e101a2a59fe110084 |
vocab.json | 566 B | 45ec1704d73046303cbd5292590b2e204b194a2d8345dfb84de81370b4ab4eef |
vocab.pkl | 3,013 B | c6700d2bbcd8dc705d6b0ca53e0f8848baa6225e9b3e836036d94ab5accd306c |
Usage
This repo is consumed by the backend via huggingface_hub.snapshot_download:
BACKEND_WEIGHTS_HUB_REPO=apoorvrajdev/captioning-inceptionv3-transformer
BACKEND_WEIGHTS_HUB_REVISION=v1.0.0
BACKEND_WEIGHTS_HUB_FILENAME=model.h5
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 30 oct
Download files
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- license: mit library_name: keras tags: - image-captioning - tensorflow - keras - transformer - inceptionv3 - multimodal - dev-scaffold pipeline_tag: image-to-text --- # Image Captioning System — Dev Scaffold (v1.0.0) InceptionV3 + Transformer image captioning architecture. This release contains a **deployment scaffold** used for end-to-end system validation and infrastructure testing. It is intentionally published before the production training run so the full serving stack (FastAPI backend, Hugging Face Spaces container, Vercel frontend, GitHub Actions CI/CD) can be exercised end-to-end. ## Purpose - FastAPI inference serving - Hugging Face Hub `snapshot_download` integration - Frontend / backend deployment validation - CI/CD pipeline validation - Production ML system architecture demonstration ## Architecture - **Encoder:** frozen InceptionV3 (ImageNet weights, 2048-dim features) - **Decoder:** single Transformer decoder layer, d_model=512, 8 heads - **Vocab size:** 52 tokens (scaffold) — production target is 15,000 (COCO) - **Max caption length:** 40 tokens ## ⚠️ Current limitations The decoder weights are **bootstrap development artefacts** generated by a synthetic 10-sentence corpus, not trained on the full COCO dataset. Caption outputs will be incoherent and limited to the 52-token scaffold vocabulary. The encoder is fully functional (real ImageNet weights); only the decoder is untrained. Future revisions will replace these weights with a model trained on MS COCO 2017 via `scripts/train.py` and `configs/train/stabilized.yaml`. ## Files | File | Size | SHA-256 | |---|---:|---| | `model.h5` | 158 MB | `bfe020d920aa2f3d019bf7b5b33904384057372e7c304a9e101a2a59fe110084` | | `vocab.json` | 566 B | `45ec1704d73046303cbd5292590b2e204b194a2d8345dfb84de81370b4ab4eef` | | `vocab.pkl` | 3,013 B | `c6700d2bbcd8dc705d6b0ca53e0f8848baa6225e9b3e836036d94ab5accd306c` | ## Usage This repo is consumed by the backend via `huggingface_hub.snapshot_download`: ```env BACKEND_WEIGHTS_HUB_REPO=apoorvrajdev/captioning-inceptionv3-transformer BACKEND_WEIGHTS_HUB_REVISION=v1.0.0 BACKEND_WEIGHTS_HUB_FILENAME=model.h5
Source context: 0 downloads · 0 likes · Pipeline image-to-text · Library keras · Repo apoorvrajdev/captioning-inceptionv3-transformer
