AI & ML interests

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AtAndDevΒ 
posted an update 3 days ago
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@Banaxi-Tech stop hiding my comments. AND STOP STEALING PAPERS AND SPREADING MISINFORMATION.
your BGA blog is a copy of NSA (deepseek, 2025) branded under your name. literally the same top16 selected blocks, 512 local window, router over block summaries, all you did was change block size from 64 to 128.
you didnt cite NSA once but you put a β€œplease cite BGA” bibtex at the bottom.
i commented under your post and said that there is no way that you can support claims like: β€œThe Accuracy Should BE WAy better than DSA but untested yet.” you didnt run a single experiment. and the 256x isnt from BGA, its just n/2k with k=2048 so the exact same k DSA uses. if opus wrote this for you, at least read it before posting.
i commented again after you hid my comment despite it having constructive and correct feedback and you hid that too. and again.
you can hide the truth and just try to get hf post likes..... but is it really the thing that needs to be done? do you really want to take papers and make them yours while barely even changing the params?

admitting your mistakes and doing something about them needs humbleness, intelligence, humanness.
i encourage you to admit your mistakes and try to do better next time (at least read what blog your ai wrote or do proper experiments to back your stuff up).
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AtAndDevΒ 
posted an update about 1 month ago
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SPECK 2 IS ALREADY OUT: specklabs/Speck2-140M

Pretrained on 4x more tokens than the previous releases (20b vs 5b).
Instruct tuned versions are coming soon.
Very interesting models are coming soon too (hint: super long context).

Thanks for everyone supporting!
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AtAndDevΒ 
posted an update about 2 months ago
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SPECK1.5 IS COMING SOON!
Same 5B token budget but much better corpus quality.

Also getting a ton of downloads, thanks for everyone downloading and liking <3

specklabs
AtAndDevΒ 
posted an update about 2 months ago
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NEW SPECK UPDATES:

Just hit #14 and #15 with out FIRST models on Open SLM Leaderboard. The models were trained on 5B tokens, while competing with similarly sized models trained on more than 6-20x the data.

A new base model Speck1.5-140M being trained right now on a higher quality corpus and will be released soon.
SpeckChat3 is coming very soon with 1 million samples, specifically designed to post train small base models.

Also, just to clarify stuff, we will NOT release anything that is NOT MIT licensed EVER. Openness is needed in small language research.

Thanks to everyone supporting the project, and stay tuned for new releases!
AtAndDevΒ 
posted an update about 2 months ago
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SPECK UPDATES:
1 New instruct model tuned on top of Speck1-140M: specklabs/Speck1-140M-Instruct
2 Instruction tuning datasets
2 GGUFs

Much more coming soon:
Speck1.1-140M-Instruct that is post trained on SpeckChat2 will be coming very soon
New base model Speck1.5-140M is coming with a much higher quality corpus

Thanks to everyone who is already supporting the project, and stay tuned for new releases!
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AtAndDevΒ 
posted an update about 2 months ago
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FIRST SPECK MODEL RELEASED:
specklabs/Speck1-140M

new models coming very soon (both instruct and much better models), with much much higher training scale as i am getting marenostrum5 access soon!
we will be looking at 100b-2t token budgets :)
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Ujjwal-TyagiΒ 
posted an update 5 months ago
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6 Open-Source Libraries to FineTune LLMs
1. Unsloth
GitHub: https://github.com/unslothai/unsloth
β†’ Fastest way to fine-tune LLMs locally
β†’ Optimized for low VRAM (even laptops)
β†’ Plug-and-play with Hugging Face models

2. Axolotl
GitHub: https://github.com/OpenAccess-AI-Collective/axolotl
β†’ Flexible LLM fine-tuning configs
β†’ Supports LoRA, QLoRA, multi-GPU
β†’ Great for custom training pipelines

3. TRL (Transformer Reinforcement Learning)
GitHub: https://github.com/huggingface/trl
β†’ RLHF, DPO, PPO for LLM alignment
β†’ Built on Hugging Face ecosystem
β†’ Essential for post-training optimization

4. DeepSpeed
GitHub: https://github.com/microsoft/DeepSpeed
β†’ Train massive models efficiently
β†’ Memory + speed optimization
β†’ Industry standard for scaling

5. LLaMA-Factory
GitHub: https://github.com/hiyouga/LLaMA-Factory
β†’ All-in-one fine-tuning UI + CLI
β†’ Supports multiple models (LLaMA, Qwen, etc.)
β†’ Beginner-friendly + powerful

6. PEFT
GitHub: https://github.com/huggingface/peft
β†’ Fine-tune with minimal compute
β†’ LoRA, adapters, prefix tuning
β†’ Best for cost-efficient training
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Ujjwal-TyagiΒ 
posted an update 6 months ago
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This is the best set of AI and ML books and a full guide to learning machine learning from the ground up. This is my study material that I used, so I thought it would be helpful to share it with others. Like, share, and add it to your collection at Ujjwal-Tyagi/ai-ml-foundations-book-collection.
Ujjwal-TyagiΒ 
posted an update 6 months ago
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We are hiring at Shirova AI. We need AI researchers and engineers to work in our research lab. Shirova AI is a research lab in India, so we can help our researchers move to nearby workspaces or let them work from home without ever coming to the lab. We're building our founding team, so the pay will be good. You can learn, so don't hesitate to mail us at: careers@shirova.com
Ujjwal-TyagiΒ 
posted an update 7 months ago
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I am sharing my study material for AI & ML, these books are really a "bible" and gives very strong foundation, I also have given guidance, introduction and my master notes in the dataset repo card! I hope you will find them helpful, if you have any queries, just start a discussion and I am always there to help you out!
Ujjwal-Tyagi/ai-ml-foundations-book-collection
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Ujjwal-TyagiΒ 
posted an update 7 months ago
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We have now LTX 2.3 with more better visual quality and richer sound, check it out! Lightricks/LTX-2.3
Ujjwal-TyagiΒ 
posted an update 8 months ago
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Public reports allege that Anthropic gobbled up trillions of tokens of copyrighted material and public data to build their castle. πŸ°πŸ“„ Now that they're sitting on top, they're begging for special laws to protect their profits while pulling the ladder up behind them. πŸͺœπŸš«

But the hypocrisy meter just broke! πŸ“‰ They are accusing Chinese labs like DeepSeek, Minimax, and Kimi of "huge distillation attacks. The Reality is that You can't just loot the entire internet's library, lock the door, and then sue everyone else for reading through the window. Stop trying to gatekeep the tech you didn't own in the first place. Read the complete article on it: https://huggingface.co/blog/Ujjwal-Tyagi/the-dark-underbelly-of-anthropic
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