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dingo-actual

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reacted to burtenshaw's post with 🤗 about 3 hours ago

SmolLM2 paper is out! 😊 😍 Why do I love it? Because it facilitates teaching and learning! Over the past few months I've engaged with (no joke) thousands of students based on SmolLM. - People have inferred, fine-tuned, aligned, and evaluated this smol model. - People used they're own machines and they've used free tools like colab, kaggle, and spaces. - People tackled use cases in their job, for fun, in their own language, and with their friends. upvote the paper https://huggingface.co/papers/2502.02737

reacted to mkurman's post with 👍 about 3 hours ago

Blurred-Thoughts Supervised-Finetuning 🙈 After hours of working with GitHub Copilot to organize the code, I'm keen to announce the release of Blurred Thoughts Supervised-Finetuning (BT-SFT), a new method for fine-tuning LLMs to produce more diverse and creative responses. BT-SFT introduces: ✅ Smart tokenization method randomly masks tokens within <think> ... </think> tags, promoting the model to generate diverse responses that align better with its probability distribution instead of memorizing the thought process from distilled data. ✅ Reward function that ensures responses are well-structured. Explore and contribute to the project available in my GitHub repository: https://github.com/mkurman/blurred-thoughts-SFT Keep me updated on your experiments with BT-SFT! 🐐

reacted to schuler's post with 👍 about 3 hours ago

📢 New Research Alert: Making Language Models Smaller & Smarter! Thrilled to share the latest technical report demonstrating how to reduce language model parameters by 77% while maintaining performance. The secret? Grouped pointwise convolutions. Yes. We brought a method from computer vision to the transformers arena. 🔑 Key Findings: • 77% parameter reduction. • Maintained model capabilities. • Improved generalization. Paper: https://www.researchgate.net/publication/388835829_SAVING_77_OF_THE_PARAMETERS_IN_LARGE_LANGUAGE_MODELS_TECHNICAL_REPORT Code: https://github.com/joaopauloschuler/less-parameters-llm

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dingo-actual's activity

upvoted a collection about 1 month ago

Dolphin 3.0

Dolphin 3.0 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model. • 9 items • Updated 8 days ago • 81

upvoted 2 collections 4 months ago

MobileLLM

Optimizing Sub-billion Parameter Language Models for On-Device Use Cases (ICML 2024) https://arxiv.org/abs/2402.14905 • 9 items • Updated Nov 27, 2024 • 104

SmolLM2

State-of-the-art compact LLMs for on-device applications: 1.7B, 360M, 135M • 16 items • Updated 8 days ago • 233

upvoted a collection 6 months ago

🪐 SmolLM

A series of smol LLMs: 135M, 360M and 1.7B. We release base and Instruct models as well as the training corpus and some WebGPU demos • 12 items • Updated Dec 22, 2024 • 214

upvoted a collection 7 months ago

Lumimaid 0.2

4 items • Updated Jul 26, 2024 • 18

upvoted a paper about 1 year ago

Trusted Source Alignment in Large Language Models

Paper • 2311.06697 • Published Nov 12, 2023 • 11

upvoted 2 papers over 1 year ago

Idempotent Generative Network

Paper • 2311.01462 • Published Nov 2, 2023 • 25

Controllable Music Production with Diffusion Models and Guidance Gradients

Paper • 2311.00613 • Published Nov 1, 2023 • 25