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username-generator
ks46/username-generator
username-generator is a text generation model from ks46. Use it when you need the model to write or continue text. It is set up for pytorch. The card lists the license as mit.
Byte-level GPTs that dream up login-style usernames (darkphoenix, Cargan66), trained on the ks46/usernames corpus. Every folder is one trained model: its checkpoint (ckpt.pt), the export for the single-threaded x86-64…
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Updated Sep 21, 2026
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18.9 GB
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.pt21.5 GB · 96%
At a glance
- Task
- Text Generation
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Sep 19, 2026
- Updated
- Sep 21, 2026
- SHA
- e6d08495
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Datasets
Model card
From the Hugging Face model README
username-generator
Byte-level GPTs that dream up login-style usernames (dark_phoenix, Cargan66), trained on the
ks46/usernames corpus. Every folder is one trained model: its checkpoint (ckpt.pt), the export
for the single-threaded x86-64 batch kernel ndgen (model-int7.ndq, model.ndq), the kernel's
golden reference NLLs, eval.json, manifest.json, samples.txt and a card with the details.
Vocabulary is 256 bytes with byte 0 as the stop token; the held-out split is
xxh3_64(name) % 64 == 0, so bits/char are comparable only between models trained on the same corpus.
| model | layers × width | params | iters | held-out bits/char | novel samples |
|---|---|---|---|---|---|
| teacher3-16x1024 | 16×1024 | 205.9M | 50,000 | 3.2067 | 90% |
| g3-6x640-a09 | 6×640 | 30.7M | 40,000 | 3.2513 | 90% |
| g3-12x256-a09 | 12×256 | 9.7M | 40,000 | 3.2891 | 91% |
| g3-6x384-a09 | 6×384 | 10.7M | 40,000 | 3.2958 | 91% |
| g3-8x256-a09 | 8×256 | 6.5M | 40,000 | 3.3178 | 92% |
| g3-12x192-a09 | 12×192 | 5.5M | 40,000 | 3.3239 | 91% |
| g3-4x384-a09 | 4×384 | 7.2M | 40,000 | 3.3369 | 91% |
| g3-6x256-a09 | 6×256 | 4.9M | 40,000 | 3.3448 | 91% |
| g3-8x192-a09 | 8×192 | 3.7M | 40,000 | 3.3586 | 92% |
| teacher2-16x1024 | 16×1024 | 205.9M | 25,000 | 3.4010 | 91% |
| g2-6x640-a09 | 6×640 | 30.7M | 40,000 | 3.4378 | 91% |
| g2-6x512-a09 | 6×512 | 19.4M | 40,000 | 3.4537 | 91% |
| g2-8x384-a09 | 8×384 | 14.3M | 40,000 | 3.4602 | 91% |
| g2-12x256-a09 | 12×256 | 9.7M | 40,000 | 3.4739 | 92% |
| g2-6x384-a09 | 6×384 | 10.7M | 40,000 | 3.4810 | 91% |
| g2-8x256-a09 | 8×256 | 6.5M | 40,000 | 3.5020 | 92% |
| g2-12x192-a09 | 12×192 | 5.5M | 40,000 | 3.5074 | 92% |
| g2-4x384-a09 | 4×384 | 7.2M | 40,000 | 3.5193 | 92% |
| g3-4x128-a09 | 4×128 | 0.8M | 40,000 | 3.5269 | 93% |
| g2-6x256-a09 | 6×256 | 4.9M | 40,000 | 3.5280 | 92% |
| g3-6x96-a09 | 6×96 | 0.7M | 40,000 | 3.5305 | 94% |
| g2-8x192-a09 | 8×192 | 3.7M | 40,000 | 3.5397 | 93% |
| prod-8x768-phase2 | 8×768 | 56.9M | 60,000 | 3.5619 | 93% |
| g2-12x128-a09 | 12×128 | 2.5M | 40,000 | 3.5705 | 93% |
| g3-3x128-a09 | 3×128 | 0.6M | 40,000 | 3.5738 | 93% |
| g3-4x96-a09 | 4×96 | 0.5M | 40,000 | 3.5920 | 94% |
| g3-8x64-a09 | 8×64 | 0.4M | 40,000 | 3.5923 | 93% |
| teacher-16x1024 | 16×1024 | 205.9M | 9,000 | 3.6068 | 94% |
| pre-6x640-a09 | 6×640 | 30.7M | 20,000 | 3.6137 | 94% |
| pre-8x512-a09 | 8×512 | 25.9M | 20,000 | 3.6138 | 95% |
| g2-8x128-a09 | 8×128 | 1.6M | 40,000 | 3.6138 | 94% |
| pre-16x320-a09 | 16×320 | 20.4M | 20,000 | 3.6145 | 95% |
| pre-12x384-a09 | 12×384 | 21.4M | 20,000 | 3.6147 | 95% |
| prod-fast-4x768-phase2 | 4×768 | 28.6M | 30,000 | 3.6154 | 94% |
| pre-10x384-a09 | 10×384 | 17.8M | 20,000 | 3.6197 | 95% |
| pre-5x640-a09 | 5×640 | 25.6M | 20,000 | 3.6206 | 94% |
| pre-6x512-a09 | 6×512 | 19.4M | 20,000 | 3.6232 | 94% |
| pre-4x768-a09 | 4×768 | 28.6M | 20,000 | 3.6247 | 94% |
| pre-8x384-a09 | 8×384 | 14.3M | 20,000 | 3.6279 | 94% |
| pre-10x320-a09 | 10×320 | 12.8M | 20,000 | 3.6295 | 95% |
| g3-6x64-a09 | 6×64 | 0.3M | 40,000 | 3.6299 | 94% |
| pre-6x448-a09 | 6×448 | 14.8M | 20,000 | 3.6312 | 95% |
| pre-12x256-a09 | 12×256 | 9.7M | 20,000 | 3.6380 | 95% |
| pre-6x384-a09 | 6×384 | 10.7M | 20,000 | 3.6423 | 95% |
| pre-4x512-a09 | 4×512 | 13.0M | 20,000 | 3.6481 | 95% |
| g3-2x128-a09 | 2×128 | 0.4M | 40,000 | 3.6572 | 93% |
| pre-8x256-a09 | 8×256 | 6.5M | 20,000 | 3.6588 | 95% |
| pre-4x384-a09 | 4×384 | 7.2M | 20,000 | 3.6730 | 95% |
| g3-4x64-a09 | 4×64 | 0.2M | 40,000 | 3.6984 | 94% |
| g2-4x128-a09 | 4×128 | 0.8M | 40,000 | 3.7052 | 93% |
| g2-8x64-a09 | 8×64 | 0.4M | 40,000 | 3.7648 | 94% |
| g3-8x32-a09 | 8×32 | 0.1M | 40,000 | 3.8129 | 95% |
| g3-2x64-a09 | 2×64 | 0.1M | 40,000 | 3.8361 | 94% |
| g3-4x32-a09 | 4×32 | 0.1M | 40,000 | 3.9393 | 95% |
| g3-1x64-a09 | 1×64 | 0.1M | 40,000 | 4.0124 | 95% |
| g3-2x32-a09 | 2×32 | 0.0M | 40,000 | 4.0682 | 96% |
Sampling
uv run python -m training.sample --ckpt <model>/ckpt.pt -n 20 --prefix dark --temperature 0.9
./ndgen gen --model <model>/model-int7.ndq -n 1000 --batch 64 --temperature 0.9 --prefix dark
- Task
- Text Generation
- Library
- pytorch
- License
- mit
- Created
- Sep 19, 2026
- Updated
- Sep 21, 2026