intsuc/Llama-3-ARDY-Mini-Core40-Browser

Llama 3 ARDY Mini Core40 Browser

Built with Meta Llama 3.

Browser-ready ONNX files for ARDY Mini, a browser-ready derivative of NVIDIA ARDY's Core40 text-to-motion model. Its Llama 3 + LLM2Vec text-conditioning path is distilled into an all-MiniLM-L6-v2-based encoder that emits the same 1,024-dimensional root and 1,024-dimensional body conditions. The ARDY motion generator is converted, not distilled, and runs locally with ONNX Runtime Web's WebGPU execution provider.

• Interactive app: ARDY Mini
• Source and reproducibility code: intsuc/ardy-mini
• Publisher/contact: intsuc, i@intsuc.dev

Files and browser selection

The app selects one variant automatically. It downloads only the selected variant and stores verified files in the browser cache.

Variant	WebGPU requirement	Compressed transfer size
fp16/	shader-f16; mixed FP16 decoder, FP32 denoiser and text encoder	652.53 MiB
fp32/	WebGPU; no optional shader feature	684.30 MiB

Each directory contains model.json.gz plus individually gzip-compressed ONNX and tokenizer transports declared by that manifest. Raw and compressed byte sizes and SHA-256 hashes are embedded in the manifests. Top-level SHA256SUMS covers every published file other than itself.

The production app should resolve files from an immutable Hub commit, not from main:

https://huggingface.co/intsuc/Llama-3-ARDY-Mini-Core40-Browser/resolve/<commit>/

Intended use

This release is intended for local, interactive generation and preview of human character motion from clear English descriptions. It supports the ARDY-Core-RP-20FPS-Horizon40 architecture, generates at 20 FPS, and is designed for the accompanying WebGPU browser runtime.

Reasonable uses include animation prototyping, character previews, games, creative tools, and motion-generation research consistent with the applicable licenses and acceptable-use policies.

Out-of-scope use

This is not intended as a safety-critical physical controller. Do not deploy it where failure could cause death, bodily injury, or material damage, including transportation, heavy machinery, critical infrastructure, or weapons. Simulation and non-safety-critical robotics research are not excluded by this statement. Uses prohibited by the Meta Llama 3 Acceptable Use Policy, the NVIDIA Trustworthy AI terms, or applicable law are outside scope.

Training corpus and transformations

The MiniLM condition encoder was trained and evaluated exclusively on English motion descriptions from NVIDIA Corporation's nvidia/SEED-Timeline-Annotations, revision b2cf916d8ef7a1e49fc4f0ce9e00c1981d3b9d8f, published under CC BY 4.0. The pinned timelines.jsonl has SHA-256 379d6a5b86cea06b7201d485d19ee53512cc58449352b3cf113a95d1d27603d8.

Preparation selects overview_description and events.description, applies Unicode NFKC and whitespace normalization, removes descriptions over 512 characters, deduplicates case- and punctuation-insensitively, groups related recordings, and creates deterministic disjoint train/validation/test groups. The resulting 64,287 unique descriptions comprise 51,482 train, 6,710 validation, and 6,095 test prompts. Dataset records and derived prompt text are not distributed in this repository.

Model lineage

• Motion base: nvidia/ARDY-Core-RP-20FPS-Horizon40, pinned in MODEL_PROVENANCE.json
• Student base: sentence-transformers/all-MiniLM-L6-v2 at 1110a243fdf4706b3f48f1d95db1a4f5529b4d41
• Teacher foundation: meta-llama/Meta-Llama-3-8B-Instruct at 8afb486c1db24fe5011ec46dfbe5b5dccdb575c2
• Teacher MNTP adapter: McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp at 31474e395ada192e8ed1586db6be79fb3b70c9c0
• Teacher supervised adapter: McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised at baa8ebf04a1c2500e61288e7dad65e8ae42601a7

The Llama, LLM2Vec, source MiniLM, original ARDY checkpoint, teacher cache, and dataset records are not included as separate files. The distributed graphs contain the converted motion model and trained student parameters needed by the browser runtime.

Evaluation

The selected 100-epoch student was chosen on the validation split. On all 6,095 held-out test descriptions, its 2,048-dimensional teacher-condition cosine was 0.97557 overall (0.97861 root and 0.97033 body).

Matched motion evaluation uses 64 held-out prompts, three seeds, 80 frames at 20 FPS, identical ARDY weights and noise, and no post-processing:

MiniLM vs teacher, same seed	Result
Global MPJPE	0.06475 m
Root-aligned MPJPE	0.03140 m
Root ADE / FDE	0.04776 m / 0.08181 m
Motion cosine	0.99635
Foot-contact agreement	0.96898

These metrics measure replacement fidelity to the Llama 3 + LLM2Vec teacher, not semantic quality against ground-truth motion. They are not comparable to paper FID or R-precision results.

The adopted mixed-FP16 policy keeps the autoregressive denoiser and text encoder byte-identical to FP32 and converts only reviewed decoder regions. In a 64-prompt × 3-seed × 5-window comparison against the FP32 browser graphs, accumulated 200-frame MPJPE was 0.265 mm mean / 0.350 mm p95, with 99.998% contact agreement. Full aggregate inputs and environment details are included under reports/.

The FP16 ablation report retains the browser model's internal pre-release ID and the manifest hashes used during that evaluation. Public-release metadata changes those manifest bytes but not the evaluated ONNX or tokenizer payloads. MODEL_PROVENANCE.json binds the report to this release using exact raw graph and tokenizer SHA-256 hashes plus the checkpoint and student identities.

Limitations

• English motion prompts are the evaluated input domain. Unusual wording, misspellings, non-English text, or motion concepts absent from training may reduce prompt adherence.
• Generated motion may exhibit foot sliding, contact errors, implausible transitions, self-intersections, drift, or prompt mismatch.
• The model is limited to the Core40 representation and the browser runtime's fixed generation schedule.
• Results are based on one deterministic training seed and the recorded hardware/software environment.
• FP16 and FP32 refer to browser graph precision, not an assurance of identical motion in every continuation; see the ablation report for measured bounds.

Terms

This is a composite model release, not a single Apache-2.0 work. Read MODEL_TERMS.md, NOTICE, and the complete texts under LICENSES/ before use or redistribution.

This model is not affiliated with or endorsed by NVIDIA, Meta, McGill University, Hugging Face, or sentence-transformers.

Reproducibility

MODEL_PROVENANCE.json records the source commit, exact upstream revisions, artifact identities, manifest hashes, and report hashes. SHA256SUMS provides a flat integrity index for the published repository. Export and release commands are documented in the source repository.