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alignment and llms.
💭
alignment and llms.
276 followers · 128 following

Achievements

Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: QuickdrawAchievement: Starstruckx2Achievement: Arctic Code Vault ContributorAchievement: Pull Sharkx2

Achievements

Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: QuickdrawAchievement: Starstruckx2Achievement: Arctic Code Vault ContributorAchievement: Pull Sharkx2

Highlights

  • Pro

Organizations

@for-ai @VectorInstitute @UTMIST

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xwinxu/README.md

I research scalable and principled methods for aligning large generative models. In the past, I worked at FAIR Labs at Meta, Google DeepMind and Stanford AI. I'm a graduate of CS, Math, and Stats at the University of Toronto where I began learning about latent variable models and probabilistic inference at the Vector Institute. I'm open to full-time ML research and engineering roles.

Like my models, I'm still learning (:

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  1. ContextualAI/HALOs ContextualAI/HALOs Public

    A library with extensible implementations of DPO, KTO, PPO, ORPO, and other human-aware loss functions (HALOs).

    Python 752 45

  2. bayeSDE bayeSDE Public

    Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

    Python 170 28

  3. google-research/cascades google-research/cascades Public

    Python library which enables complex compositions of language models such as scratchpads, chain of thought, tool use, selection-inference, and more.

    Python 197 14

  4. ermongroup/self-similarity-prior ermongroup/self-similarity-prior Public

    Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations

    Jupyter Notebook 25 4

  5. variational-mnist variational-mnist Public

    Fitting a recognition model (VAE) to do approximate inference on intractable posteriors of probabilistic models using an ELBO estimator.

    Python 10 1

  6. pruning-neural-nets pruning-neural-nets Public

    Generating structured sparsity in neural networks using weight and unit pruning techniques.

    Python 1