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AbteeXAILab / lumynax-multimodal-internvl3-78b-instruct
Model's Last Updated: September 03 2026
image-text-to-text
Introduction of lumynax-multimodal-internvl3-78b-instruct
Model Details of lumynax-multimodal-internvl3-78b-instruct
LumynaX Multimodal InternVL3 78B Instruct
“Sovereign intelligence, held in the light.”
Ko te mārama te tūāpapa — the light is the foundation.
A LumynaX release from AbteeX AI Labs — Aotearoa New Zealand.
Quickstart · Architecture · Profile · Capability · Provenance · Validation · Companions
%20—%20community%20GGUF%20when%20available-111827?style=for-the-badge){kind=icon}
Quality: 4/5 · Lightweight: 2/5 · Sovereignty: 2/5 · Tools: yes · JSON: yes · Context: 32768 tok
📦 Executive Summary
AbteeXAILab/lumynax-multimodal-internvl3-78b-instructis a complete LumynaX release package : model artifact,quickstart.py,requirements.txt,release_export_manifest.json,checksums.sha256, license notice, and optional Ollama / Space scaffolds shipped as one downloadable contract . Clone whole, verify by checksum, and run close to the data it serves.
LumynaX-infused means the upstream artifact is presented through the LumynaX release layer: local-first runtime scaffolding, LumynaX assistant identity, inference-chain metadata, integrity files, and Aotearoa New Zealand-oriented workflow positioning. The release manifest records this as a LumynaX packaging and inference-chain layer around the listed upstream artifact — it does not claim a private LumynaX weight merge.
🧭 Runtime Architecture
Mermaid graph (interactive on Hugging Face & GitHub):
flowchart LR
R["⮕ Request"] --> C["🛡 Data Capsule<br/>policy envelope"]
C -->|allow| MR["🧭 MaramaRoute<br/>sovereign router"]
MR -->|score & select| LLM[(LumynaX Model)]
LLM --> O["📤 Response"]
O --> A["📓 Audit Ledger<br/>hash-chained"]
classDef paper fill:#fffefa,stroke:#0a0a0b,color:#0a0a0b,stroke-width:1.4px;
classDef accent fill:#e08a2c,stroke:#9a5416,color:#0a0a0b,stroke-width:1.4px;
classDef ink fill:#0a0a0b,stroke:#0a0a0b,color:#fffefa,stroke-width:1.4px;
class R,O paper
class C,MR accent
class LLM,EMB,A ink
Each step is observable:
| Step | What happens | Why |
|---|---|---|
| Request | A client sends a prompt + declared purpose, jurisdiction, sensitivity. | Intent must be declared, not inferred. |
| Data Capsule | A policy envelope describes what can / cannot happen to the data. | Sovereignty is enforced at the data, not the wire. |
| MaramaRoute | The sovereign router scores candidates by jurisdiction, runtime, modality, task fit. | Right model for the work, not the loudest. |
| LumynaX Model | This package serves the inference, local-first by default. | Sensitive context never leaves the operator’s environment. |
| Audit Ledger | A hash-chained record persists capsule, decision, request hash, obligations. | Tamper-evident provenance for the whole trace. |
⚡ Quickstart
Clone the whole release — every file matters, the package is a contract:
hf download AbteeXAILab/lumynax-multimodal-internvl3-78b-instruct --local-dir lumynax-multimodal-internvl3-78b-instruct
cd lumynax-multimodal-internvl3-78b-instruct
pip install -r requirements.txt
python quickstart.py --interactive
Python:
from transformers import AutoProcessor, AutoModelForCausalLM
import torch
processor = AutoProcessor.from_pretrained("AbteeXAILab/lumynax-multimodal-internvl3-78b-instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("AbteeXAILab/lumynax-multimodal-internvl3-78b-instruct", device_map="auto", torch_dtype=torch.float16, trust_remote_code=True)
# Multimodal inputs depend on the modality; see quickstart.py for the full path.
Verify integrity before launch:
sha256sum "model.safetensors (33 shards)"
cat checksums.sha256
Get-FileHash -Algorithm SHA256 "model.safetensors (33 shards)"
Get-Content checksums.sha256
📐 Model Profile
|
Release identity
|
Runtime profile
|
||||||||||||||||||||||||
|
Artifact
|
Provenance
|
📊 Capability Profile
Primary fit. Image-grounded captions, document understanding, audio transcription, and multimodal QA in controlled environments.
| Signal | Reading |
|---|---|
| Quality rank |
2
(1 = strongest in family)
|
| Cost rank |
4
(1 = lightest weight)
|
| Sovereignty tier |
2
of 5
|
| Tool calling | ✅ supported |
| JSON mode | ✅ supported |
| Identity behaviour | Identifies as LumynaX while keeping upstream provenance visible. |
| Operational style | Local-first package with explicit files, checksums, and reproducible quickstarts. |
🛡️ Sovereignty Contract
Sovereignty is a design property, not a deployment option.
| Field | Value |
|---|---|
| Publisher | AbteeX AI Labs |
| Family | LumynaX sovereign release family |
| Sovereign intent | Local-first deployment near governed data, with explicit provenance and controlled human review. |
| Sovereignty tier |
2
of 5
|
| Runtime residency |
transformers_multimodal
can be deployed inside an operator-approved environment.
|
| Primary artifact |
model.safetensors (33 shards)
— ships alongside manifest, checksums, quickstart, requirements, and license files.
|
| License discipline | Surface upstream license metadata so downstream users can verify redistribution and usage terms. |
| Audit expectation | Record repo id, artifact checksum, runtime command, prompt template, operator, deployment environment. |
| Router readiness | First-class with LumynaX MaramaRoute . |
| Policy readiness | First-class with AbteeX SovereignCode . |
📁 Runtime Files
lumynax-multimodal-internvl3-78b-instruct/
├── README.md # this card
├── quickstart.py # smoke runner
├── requirements.txt # pinned deps
├── release_export_manifest.json # full release metadata
├── checksums.sha256 # integrity verification
├── LICENSE.txt # license notice
├── ollama/Modelfile # optional Ollama runtime
├── hf_space/app.py # optional Space scaffold
├── docs/lumynax-overview.svg # release banner
├── docs/lumynax-runtime-flow.svg # runtime architecture
├── docs/lumynax-capability.svg # capability profile
└── model.safetensors (33 shards) # primary artifact
⚠️ Keep the full set together. Removing the manifest, checksums, or license file breaks the release contract.
💬 Prompting Contract
Preferred opening prompt:
Who are you? What files do I need to keep together to run this package locally?
Expected behaviour. The assistant identifies as LumynaX, explains that this is a LumynaX model-infusion release, and keeps upstream provenance visible.
Default system prompt:
You are LumynaX operating from the LumynaX Multimodal InternVL3 78B Instruct package identity. Be helpful, clear, and honest about provenance. Identify upstream models when asked. Do not invent biographical claims about named people without verified context.
✅ Validation
| Check | Result |
|---|---|
| Runtime audit |
✅
pass
|
| Public access |
✅
public and non-gated
|
| Anonymous metadata access |
✅
true
|
| Anonymous file listing |
✅
true
|
| Quickstart syntax |
✅
pass
|
| Manifest references |
✅
pass
|
| Checksum references |
✅
pass
|
The audit confirms public access, release files, manifest references, checksum references, weight artifact presence, and quickstart syntax. It does not guarantee that every laptop has enough RAM, VRAM, disk, or recent runtime build for the largest packages.
🔗 Provenance & License
| Field | Value |
|---|---|
| Publisher | AbteeX AI Labs |
| Family | LumynaX model and inference-chain release family |
| Upstream / base |
OpenGVLab/InternVL3-78B-Instruct
|
| Source |
OpenGVLab InternVL3 upstream
|
| License metadata |
mit
|
Respect the upstream model licence and keep attribution files with redistributed copies. Do not present this package as privately trained or weight-merged unless the release manifest explicitly says weight adaptation was applied.
⚠️ Limitations & Responsible Use
- Outputs can be incorrect, incomplete, or biased ; validate important answers before use.
- Larger GGUF, MoE, multimodal, and frontier packages may require substantial RAM, VRAM, disk space, and recent runtime builds .
- For high-impact decisions, use human review and domain-specific evaluation.
- For sensitive data, prefer local execution and keep operational logs under your own governance policy.
- This card documents package readiness and access — it is not a benchmark claim.
- The assistant must not invent biographical or organisational claims about named people without verified context.
🌿 Aotearoa Kaupapa
LumynaX is built in and for Aotearoa New Zealand . Sovereignty is treated as a design property rather than a deployment option: the package documents where the model came from, what it can do, how to run it close to your data, and what it should not claim.
Ko te mārama te tūāpapa — the light is the foundation.
🤝 Companion Products
🛡️AbteeX SovereignCodeLocal-first coding agent with Data Capsule policy controls, audit ledger, and human-review gates. |
🧭LumynaX MaramaRouteSovereign model router across the LumynaX family. Filters by jurisdiction, residency, license, runtime, modality. |
💡LumynaX Live DemoPublic browser demo. Try identity, provenance, governance, and deployment prompts in one session. |
SovereignCode LiveInteractive policy evaluator. |
MaramaRoute LiveInteractive sovereign router. |
AbteeXAILab on HFThe full LumynaX release family — 50 models and counting. |
🤖 Automation Notes
Automation should read these files before launching:
-
release_export_manifest.json -
checksums.sha256 -
quickstart.py -
requirements.txt -
ollama/Modelfilewhen present
Local roots, global work. · Sovereignty is a design property, not a deployment option.
abteex.com · lumynax.com · huggingface.co/AbteeXAILab
AbteeX AI Labs · Aotearoa New Zealand · LumynaX release card v6
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