Statistics for topic transformers

Lumina-T2X is a unified framework for Text to Any Modality Generation

Unify Efficient Fine-Tuning of 100+ LLMs

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan...

CVPR 2024 论文和开源项目合集

Lumina-T2X is a unified framework for Text to Any Modality Generation

Implementation of Alphafold 3 in Pytorch

Unified Training of Universal Time Series Forecasting Transformers

[CVPR 2024] Official implementation of the paper "Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement"

The PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling

Lumina-T2X is a unified framework for Text to Any Modality Generation

Unify Efficient Fine-Tuning of 100+ LLMs

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan...

Lumina-T2X is a unified framework for Text to Any Modality Generation

LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.

The PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling

Implementation of Alphafold 3 in Pytorch

A curriculum for learning about foundation models, from scratch to the frontier

The PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling

Implementation of Alphafold 3 in Pytorch

Implementation of Infini-Transformer in Pytorch

Exploration into the proposed "Self Reasoning Tokens" by Felipe Bonetto

Unify Efficient Fine-Tuning of 100+ LLMs

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan...

[GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly y...

Lumina-T2X is a unified framework for Text to Any Modality Generation

A curriculum for learning about foundation models, from scratch to the frontier

Implementation of Alphafold 3 in Pytorch

Unofficial PyTorch/🤗Transformers(Gemma/Llama3) implementation of Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

Implementation of Infini-Transformer in Pytorch

Exploration into the proposed "Self Reasoning Tokens" by Felipe Bonetto

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

Unify Efficient Fine-Tuning of 100+ LLMs

OpenChat: Advancing Open-source Language Models with Imperfect Data

Robust recipes to align language models with human and AI preferences

Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan...

Unify Efficient Fine-Tuning of 100+ LLMs

Machine Learning Engineering Open Book

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

Unify Efficient Fine-Tuning of 100+ LLMs

🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalab...

An Easy-to-use, Scalable and High-performance RLHF Framework (Support 70B+ full tuning & LoRA & Mixtral & KTO)

ML-powered speech recognition directly in your browser