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mkurman 
posted an update about 1 month ago
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# SYNTHLabs

Symbolic reasoning dataset creator & curator.

- Generator: create your own dataset from scratch
- Converter: use existing datasets (Hugging Face support) with reasoning traces to match our SYNTH style
- DEEP Mode: multiple agents working together in various configurations
- Multi-turn Support: pass one DEEP run, let the model ask follow-up questions, and choose who should respond using SYNTH-like thinking
- Firebase/Firestore: download your data directly as a JSONL file or upload it to your Firestore (production mode)
- Data Preview: Have data but unsure what's inside? Explore it directly!
- Verifier View: evaluate generated data, remove duplicates, assign ratings

and many more!

GitHub: https://github.com/mkurman/synthlabs

Dataset:
mkurman/medical-SYNTH-reasoning-preview
mkurman 
posted an update 7 months ago
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757
🚀 Big news! NeuroBLAST, the outstanding new architecture, has officially arrived on HF! After three intense months of training my 1.9 billion SLM on my trusty RTX 3090 Ti, I’m happy to announce the results. While it’s not perfect just yet, I’ve dedicated countless hours to optimizing costs while crafting clever layer connections that mimic the brain's centers. Plus, I’ve introduced a new memory-like layer that’s sure to turn heads! I can’t wait to dive deep into this journey in my upcoming blog post. Stay tuned for the full scoop! 🔥

meditsolutions/NeuroBLAST-1.9B-Instruct-Early-Preview
mkurman 
updated a model 7 months ago
mkurman 
updated a collection 7 months ago
mkurman 
published a model 7 months ago
mkurman 
updated a model 7 months ago
mkurman 
posted an update 12 months ago
mkurman 
updated a collection 12 months ago
mkurman 
in meditsolutions/medit-one-140M-9B-tokens-checkpoint 12 months ago

Question on meaning of parameter of this model

2
#2 opened 12 months ago by
JLouisBiz
mkurman 
posted an update 12 months ago
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943
Just released NVAMP Loss!

✔️ modification of the cross-entropy loss function designed specifically for training LLMs.
✔️ twist on the standard cross-entropy loss by emphasizing the importance of outlier prediction errors and dynamically normalizing token-level variance.
✔️ more stable and efficient training, leading to models that generalize better.

Check it out, give it a spin, and let me know what you think!

Licensed under the Apache 2.0 license and ready to use. Happy training! 🔥🤖

https://github.com/mkurman/nvamp-loss
mkurman 
in meditsolutions/medit-one-140M-9B-tokens-checkpoint 12 months ago

Can't install

2
#1 opened 12 months ago by
JLouisBiz
mkurman 
posted an update 12 months ago
mkurman 
published a model 12 months ago
mkurman 
posted an update 12 months ago
mkurman 
posted an update 12 months ago
mkurman 
updated a model 12 months ago
mkurman 
published a model 12 months ago
mkurman 
posted an update 12 months ago
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3719
Introducing a new architecture, MedIT One – a single-token transformer with LSTM-like recurrence.

It is extremely fast in training and inference, but we lack funding for large-scale training. Enjoy 🍓

https://github.com/MedITSolutionsKurman/medit-one
mkurman 
posted an update about 1 year ago
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2054
I've been working on something cool: a GRPO with an LLM evaluator that can also perform SFT on the feedback data - if you want. Check it out 😊

Any 🌟are more than welcome 🤗

https://github.com/mkurman/grpo-llm-evaluator