MatterWaveAI/grt-20m-base
text-generation model by MatterWaveAI
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
A Geometric Rotation Transformer pretrained on a mix of eight English corpora, including FineWeb-Edu, Cosmopedia, and FineMath. GRT replaces the dense linear projections of a standard transformer with cascades of learned Givens rotations on SO(D), so the residual path contains no nn.Linear at all. This is a research preview at small scale. It is published to demonstrate that the architecture trains stably and evaluates end-to-end through the same OpenAI-HTTP serving seam as every other model, and to give CPU-only CI a cheap, always-available upstream. Parameter counts are measured from the published model.safetensors. "20m" is the size-class label, not a parameter count. The embedding dominates: 6.45M of 16.7M parameters are the token embedding (50,000 tokens x 128 phase angles, plus a log-magnitude per token). The three reference completions, generated by the published weights through transformers f32, and reproduced token-for-token identically by the vLLM and llama.cpp serving paths: Evaluated via grt-slm-bench (training/slmbench.py)…
Read the full model card ↗ · Preview checked 2026-11-07T08:10:06.136Z
Inside the original model card — Document outline
- GRT-20M-Base (NeurIPS Submission Pretrained Checkpoint)
- Model Details
- Training
- Sample output (greedy, temperature 0)
- Benchmarks (Pre-Fine-Tune Zero-Shot & Standard PairAdam Baseline)
- Usage
- GGUF
- Architecture
- Intended Use & Limitations
- Citation
- License
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
MatterWaveAI/grt-20m-base is a text-generation model repository published by MatterWaveAI on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 16,730,832
- Architecture
- GRTForCausalLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-11-07T06:36:41.000Z
- Last modified
- 2026-11-07T06:36:42.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-07T06:54:27.277Z. Daily imports are snapshots, not real-time monitoring.
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