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quecto mode
227.6
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appvoid
appvoid
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https://ko-fi.com/appvoid
appvoidofficial
appvoid
AI & ML interests
singularity through byte-level tokens and small language models - creating applications and ideas out of the void
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We’ve been cooking something new at Bench Labs. Introducing Cagliostro-v3, our new 146M parameter language model trained completely from scratch. The run isn’t even finished yet. At the current checkpoint: • 146M parameters • 72.7B / 75B tokens trained • 26.27 Open SLM Index • 43.80 ArithMark-3 • Trained on a single RTX 5090 • ~90K to 103K tokens/sec during training • ~9 days for the full run • Apache 2.0 For some context, SmolLM2-135M scores 27.13 on the same Index after being trained on roughly 2 trillion tokens. Cagliostro-v3 is currently at 26.27 with only ~72.7B. That’s around 27x fewer training tokens. The model also currently Hold the number 3rd spot for ArithMark-3, scoring 43.80 This wasn’t achieved by just throwing more tokens at the model. A huge part of v3 has been figuring out architecture, data mixture, and training dynamics at this scale. The model uses a custom 30-layer decoder architecture with grouped-query attention and cross-head subspace attenuation, SwiGLU, RMSNorm, RoPE, tied embeddings, and a warmup-stable-decay training schedule. During cooldown we also substantially shifted the data mixture toward higher-quality synthetic textbook and mathematics data, with the mathematics share increasing from 10% to 28%. And everything is open. The repository contains the training history with checkpoints pushed roughly every 30 minutes, so you can inspect how the model evolved throughout training rather than only seeing the final weights. This is still a pre-final checkpoint. We have roughly 2.3B tokens left and the learning-rate cooldown is still running. So 26.27 isn’t the final number. Really excited to see where the last part of the run lands. Cagliostro-v3: https://huggingface.co/bench-labs/cagliostro-v3 Built by Bench Labs. Open SLM Leaderboard: https://huggingface.co/spaces/AxiomicLabs/Open_SLM_Leaderboard
updated
a dataset
about 3 hours ago
dotlabs/rewrite
published
a dataset
about 15 hours ago
appvoid/void-byte-data
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Organizations
appvoid
's models
461
Sort: Recently updated
appvoid/cortex
Text Generation
•
9.35M
•
Updated
about 17 hours ago
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700
appvoid/void.0
0.1B
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Updated
13 days ago
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206
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4
appvoid/bet-10m
Text Generation
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10.9M
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Updated
13 days ago
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1.11k
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3
appvoid/char-core
47.3M
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Updated
19 days ago
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273
appvoid/corebox
Text Generation
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47.3M
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Updated
19 days ago
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449
appvoid/picollama
35.2M
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Updated
20 days ago
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65
appvoid/palmer-007
91.1M
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Updated
Aug 9
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43
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3
appvoid/palmer-006
Text Generation
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91.1M
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Updated
Aug 9
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432
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10
appvoid/bytebox
Updated
Aug 6
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18
appvoid/palmer-007-preview
Text Generation
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91.1M
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Updated
Aug 3
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41
appvoid/a-cool-model
Text Generation
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0.4B
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Updated
Jul 27
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26
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2
appvoid/v118-round-02
Text Generation
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0.4B
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Updated
Jul 24
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10
appvoid/v118-dpo-round-01
Text Generation
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0.4B
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Updated
Jul 12
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14
appvoid/v118
0.4B
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Jul 12
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14
appvoid/cloud-v3
Text Generation
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0.4B
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Jul 11
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19
appvoid/cloud-v1
Text Generation
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0.4B
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Jul 11
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14
appvoid/cloud-11
Text Generation
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0.4B
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Jul 6
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14
appvoid/cloud-10
Text Generation
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0.4B
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Jul 6
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18
appvoid/cloud-09
Text Generation
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0.4B
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Jul 6
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18
appvoid/cloud-08
Text Generation
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0.4B
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Jul 6
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18
appvoid/cloud-07
Text Generation
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0.4B
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Jul 6
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16
appvoid/cloud-06
Text Generation
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0.4B
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Jul 6
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18
appvoid/cloud-05
Text Generation
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0.4B
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Jul 6
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17
appvoid/appvoid-cloud-04-q8_0-GGUF
0.4B
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Updated
Jul 6
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37
appvoid/cloud-04
Text Generation
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0.4B
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Updated
Jul 6
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16
appvoid/appvoid-cloud-03-q8_0-GGUF
0.4B
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Updated
Jul 6
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17
appvoid/cloud-03
Text Generation
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0.4B
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Updated
Jul 6
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17
appvoid/appvoid-cloud-02-q8_0-GGUF
0.4B
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Updated
Jul 6
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18
appvoid/cloud-02
Text Generation
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0.4B
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Jul 6
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16
appvoid/appvoid-palmer-005-core-q8_0-GGUF
Text Generation
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0.4B
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Updated
Jul 6
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41
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