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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Fast-stable-diffusion, +25-50% speed increase + memory efficient + DreamBooth.
The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together.
Fujitsu Research's post-training quantization pipeline for LLMs (QEP, AutoBit, JointQ, rotation) with vLLM plugin (arXiv:2603.28845).
Friendly machine learning for the web!
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
Discover the large language models examples with insights on business adoption, language model training, and influential models.
Open source, high performance fine tuning as a service for GPT4 quality models with 5x lower latency and 3x lower cost.
Secure zero-knowledge encrypted file sharing (AES-256-GCM in-browser). No account required, MIT licensed, self-hostable, optional link expiry.
Python package which helps to debug machine learning classifiers and explain their predictions.
A deep learning-based translation library between 50 languages, built with transformers.
Train and run a computer vision model with 5-10 lines of code.
Enjoy unlimited API calls with Serverless AI Workers/LLMs for just $25 per month. No rate or concurrency limits.
Teaching LLMs memory management for unbounded context [[demo page]](https://memgpt.ai/) [[arxiv]](https://arxiv.org/abs/2310.08560).
A8e70ca5a9942e399a04543b16dff92c65bd6a94b4a8fe97253e51bfff480743.
Open Code LLMs for Code Understanding and Generation.
Advances in Evolutionary Algorithms. Edited by: Witold Kosinski. ISBN 978-953-7619-11-4, PDF ISBN 978-953-51-5796-0, Published 2008-11-01.
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559574 is an AI tool or resource for chat, research, automation, media generation, or model development.
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Creates or edits images with generative models and visual controls.
Conditioning video frames with Stable Diffusion by @devdef.