---
language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - arriella
  - infinidev
  - documentation
  - technical-report
  - model-card
  - local-llm
  - not-for-inference
pretty_name: Arriella Fleet Documentation
---

# Arriella Fleet Documentation

> **This Hub “model” contains documentation only — no neural network weights.**
> It is the public library for the Arriella fleet: papers, whitepaper, model cards, fleet spec, benchmarks, and guides.
> Inference weights (when published) will be separate model repos.

| | |
|--|--|
| Organization | **Infinidev Corp** |
| Authors / leads | **Beelzebub4888**, **Tcoder** |
| Hub user | [`UnaverageTech411`](https://huggingface.co/UnaverageTech411) |
| Contact | https://formsubmit.co/el/sumuhu |

## Why a model repo?

Hugging Face discovers technical material through model/dataset cards. Until papers have arXiv IDs (and appear on [HF Papers](https://huggingface.co/papers)), this repository is the single place to read the full Arriella documentation set. After arXiv acceptance, Paper Pages will be linked from here and from weight repos.

**Spaces** remain for runnable demos only. **This repo** is the docs library.

## Fleet at a glance

| Product | Role | Card |
|---------|------|------|
| **Flagship** | General ops (primary) | [`model-cards/flagship.md`](model-cards/flagship.md) |
| **Growth** | Domain / instruction growth | [`model-cards/growth.md`](model-cards/growth.md) |
| **Ascension** | Native DeepSeek-style reasoning | [`model-cards/ascension.md`](model-cards/ascension.md) |
| **Scout** | Edge / low-VRAM (under-recovered) | [`model-cards/scout.md`](model-cards/scout.md) |
| **Grapevine** | Omni multimodal *extension* | [`model-cards/grapevine.md`](model-cards/grapevine.md) |

Canonical identity sheet: [`fleet-spec.md`](fleet-spec.md)

## Start reading

1. [`whitepaper.md`](whitepaper.md) — product thesis  
2. [`papers/01-fleet-factory/paper.md`](papers/01-fleet-factory/paper.md) — factory technical report  
3. [`papers/02-grapevine/paper.md`](papers/02-grapevine/paper.md) — Grapevine Omni report  
4. [`benchmarks.md`](benchmarks.md) — measured results  
5. [`model-cards/`](model-cards/) — per-tier cards  

### Full paper set (`papers/`)

| Folder | Topic |
|--------|--------|
| `01-fleet-factory` | Local fleet factory |
| `02-grapevine` | Omni multimodal extension |
| `03-eat-system` | Honest weight ingest / distill |
| `04-multimodal-routing` | Caption-routed vision for text tiers |
| `05-evaluation` | Gates, gauntlets, bakeoffs |
| `06-reasoning-format` | Think / answer wire format |
| `07-mip` | Model Interior Projection |

arXiv submission notes: [`papers/SUBMISSION.md`](papers/SUBMISSION.md)

### Guides

- [`guides/fleet-training.md`](guides/fleet-training.md)
- [`guides/eat-system.md`](guides/eat-system.md)
- [`guides/grapevine.md`](guides/grapevine.md)
- [`guides/mip-viewer.md`](guides/mip-viewer.md)
- [`guides/reasoning-format.md`](guides/reasoning-format.md)

### Extra

- [`grapevine-benchmark-narrative.md`](grapevine-benchmark-narrative.md) — Grapevine vs Flagship smoke  
- [`multimodal.md`](multimodal.md) — multimodal architecture  
- [`hf-card-stubs/`](hf-card-stubs/) — YAML stubs for future weight repos  

## Honest limitations

- No weights in this repository — do not load it with `AutoModel`.
- Scout is not demo-ready; Ascension is not automatically smarter than Flagship.
- Grapevine is a technical preview multimodal extension (no Inkling weights).
- Headline benchmarks are single-workstation (RTX 5060 8 GB).

## Citation

```bibtex
@misc{arriella2026docs,
  title        = {Arriella Fleet Documentation},
  author       = {Beelzebub4888 and Tcoder},
  year         = {2026},
  howpublished = {Infinidev Corp / Hugging Face},
  url          = {https://huggingface.co/UnaverageTech411/arriella-docs},
  note         = {Documentation collection; see papers/ for technical reports}
}
```