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In a Training Loop 🔄
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Nishith Jain
KingNish
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kingnish24
KingNish24
AI & ML interests
AI is fun actually.
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New Book: No-Blackbox, Secure, Efficient AI and LLM Solutions https://mltblog.com/4aRwvM5 Large language models and modern AI is often presented as technology that needs deep neural networks (DNNs) with billions of Blackbox parameters, expensive and time consuming training, along with GPU farms, yet prone to hallucinations. This book presents alternatives that rely on explainable AI, featuring new algorithms based on radically different technology with trustworthy, auditable, fast, accurate, secure, replicable Enterprise AI. Most of the material is proprietary and made from scratch, showcasing the culmination of decades of research away from standard models to establish a new framework in machine learning and AI technology. I discuss an efficient DNN architecture based on a new type of universal functions in chapter 4, with DNN distillation and protection via watermarking in chapter 5. Then, in chapter 6, I discuss non-DNN alternatives that yield exact interpolation on the training set yet benefit from benign overfitting in any dimension. Accurate predictions are obtained with a simple closed-form expression, without gradient descent or other iterative optimization technique, essentially without training. Case studies include 96% correct predictions for the next token on a Nvidia PDF repository, automated heart beat clustering and unusually high data compression rates (big data), anomaly detection and fraud litigation linked to large-scale cybsersecurity breach (large Excel repository, automated SQL, time series and geospatial data) as well as predicting next sequence on real-world genome data with home-made LLM technology. Some datasets with 1000 dimensions are generated with the best and fastest tabular data synthesizer on the market, described in details in chapter 2 along with the best model evaluation metric. These cases correspond to different agents linked to the xLLM technology (extreme LLM) developed by the author.
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KingNish
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KingNish/ministral3-3b-hinglish-test
Image-to-Text
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4B
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Updated
Dec 4, 2025
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9
KingNish/Qwen2.5-infill-test
Text Generation
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0.5B
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Updated
Nov 30, 2025
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4
KingNish/hinglish-test
Text Generation
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0.6B
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Updated
Nov 25, 2025
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9
KingNish/Miro-test
Text Generation
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2B
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Updated
Nov 24, 2025
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10
KingNish/Qwen3-0.6b-hinglish-2
Text Generation
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0.6B
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Updated
Nov 18, 2025
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3
KingNish/Qwen3-0.6b-hinglish
Updated
Nov 18, 2025
KingNish/Deepseek-3b-A0.5B
Feature Extraction
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3B
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Updated
Oct 21, 2025
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7
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1
KingNish/Qwen-Image
Text-to-Image
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Updated
Sep 8, 2025
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5
KingNish/whisper-small-en
Automatic Speech Recognition
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0.2B
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Updated
Jul 8, 2025
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32
KingNish/moonshine-tiny-svarah
Updated
Jun 22, 2025
KingNish/tiny-talker
Updated
Jun 1, 2025
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5
KingNish/Qwen2.5-0.5b-Test-ft
Text Generation
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0.5B
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Updated
Apr 28, 2025
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578
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12
KingNish/Qwen2.5-0.5b-RBase
Text Generation
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0.5B
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Updated
Apr 28, 2025
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13
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1
KingNish/Reasoning-0.5b
Text Generation
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0.5B
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Apr 28, 2025
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38
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31
KingNish/Smollm-135M-audio
Text Generation
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Updated
Apr 22, 2025
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6
KingNish/qwen-1b-continued-v2.2
Text Generation
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1B
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Updated
Mar 9, 2025
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7
KingNish/qwen-1b-continued-v2.1
Text Generation
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1B
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Mar 8, 2025
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7
KingNish/qwen-1b-continued-v2
Text Generation
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1B
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Mar 7, 2025
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5
KingNish/qwen-1b-continued
Text Generation
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1B
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Updated
Mar 7, 2025
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9
KingNish/modernbert
Fill-Mask
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0.1B
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Updated
Feb 14, 2025
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6
KingNish/Reasoning-Llama-3b-v0.2
Text Generation
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3B
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Updated
Oct 27, 2024
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12
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4
KingNish/Reasoning-Llama-3b-v0.1
Text Generation
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3B
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Updated
Oct 12, 2024
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18
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10
KingNish/Reasoning-Llama-1b-v0.1
Text Generation
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1B
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Updated
Oct 10, 2024
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33
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26
KingNish/Llama-3.2-1B-Instruct
Text Generation
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1B
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Updated
Oct 6, 2024
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16
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1
KingNish/Qwen2.5-0.5b-Test-ft-Q4_K_M-GGUF
0.5B
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Updated
Sep 27, 2024
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4
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1
KingNish/Better-SDXL-Lora
Text-to-Image
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Updated
Jul 12, 2024
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68
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15