AAJ007/kiyotaka-ayanokoji-56m
AI model by AAJ007
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Model card & documentation
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A 10-layer, 640-wide decoder-only transformer trained from random initialisation on a single 6 GB RTX 4050 laptop GPU. No pretrained weights, no fine-tuning of an existing model: the architecture, BPE tokenizer, pretraining corpus and SFT data were built for this project. (domain) → character chat SFT Held-out character eval (60 prompts, local Qwen2.5-1.5B judge, 1–5): fidelity 3.07, coherence 3.27; with optional retrieval memory 3.02 / 3.35. Single-stream GPU decode: 277 tok/s; CPU int8: 322 tok/s at 20 MB. Training…
Read the full model card ↗ · Preview checked 2026-10-29T03:29:47.640Z
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Model overview
AAJ007/kiyotaka-ayanokoji-56m is a task-unspecified model repository published by AAJ007 on Hugging Face. The source reports the pytorch library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- Not reported
- Library
- pytorch
- Recent downloads (30 days)
- 0
- Cumulative likes
- 1
- Hugging Face trending score
- 1
- Reported safetensors parameters
- 57,193,600
- Architecture
- KiyotakaForCausalLM
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-10-20T06:25:38.000Z
- Last modified
- 2026-10-20T06:30:56.000Z
Compatibility and lineage
Language coverage was not reported.
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 2026-10-20T06:43:37.702Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.