craffel / comp664-deep-learning-spring-2023Links
Course repository for the Spring 2023 COMP664 course "Deep Learning" at UNC
☆15Updated 2 years ago
Alternatives and similar repositories for comp664-deep-learning-spring-2023
Users that are interested in comp664-deep-learning-spring-2023 are comparing it to the libraries listed below
Sorting:
- Engineering the state of RNN language models (Mamba, RWKV, etc.)☆32Updated last year
- [COLM 2024] Early Weight Averaging meets High Learning Rates for LLM Pre-training☆17Updated last year
- Demonstration that finetuning RoPE model on larger sequences than the pre-trained model adapts the model context limit☆62Updated 2 years ago
- QAmeleon introduces synthetic multilingual QA data using PaLM, a 540B large language model. This dataset was generated by prompt tuning P…☆34Updated 2 years ago
- Exploration into the proposed "Self Reasoning Tokens" by Felipe Bonetto☆57Updated last year
- ☆52Updated last year
- Embedding Recycling for Language models☆38Updated 2 years ago
- Code for the examples presented in the talk "Training a Llama in your backyard: fine-tuning very large models on consumer hardware" given…☆14Updated 2 years ago
- My explorations into editing the knowledge and memories of an attention network☆34Updated 2 years ago
- This is a new metric that can be used to evaluate faithfulness of text generated by LLMs. The work behind this repository can be found he…☆31Updated 2 years ago
- Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing☆50Updated 3 years ago
- ResiDual: Transformer with Dual Residual Connections, https://arxiv.org/abs/2304.14802☆96Updated 2 years ago
- 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.☆81Updated 3 years ago
- Source-to-Source Debuggable Derivatives in Pure Python☆15Updated last year
- ☆22Updated 10 months ago
- Implementation of N-Grammer, augmenting Transformers with latent n-grams, in Pytorch☆76Updated 2 years ago
- Explorations into adversarial losses on top of autoregressive loss for language modeling☆38Updated 7 months ago
- Repository containing awesome resources regarding Hugging Face tooling.☆48Updated last year
- Minimum Description Length probing for neural network representations☆20Updated 8 months ago
- PyTorch Implementation of the paper "MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training"☆24Updated this week
- Some personal experiments around routing tokens to different autoregressive attention, akin to mixture-of-experts☆119Updated last year
- ☆26Updated last year
- ☆33Updated 2 years ago
- Training and evaluation code for the paper "Headless Language Models: Learning without Predicting with Contrastive Weight Tying" (https:/…☆27Updated last year
- Triton Implementation of HyperAttention Algorithm☆48Updated last year
- Latent Diffusion Language Models☆68Updated 2 years ago
- Experimental scripts for researching data adaptive learning rate scheduling.☆22Updated 2 years ago
- This library supports evaluating disparities in generated image quality, diversity, and consistency between geographic regions.☆20Updated last year
- Implementation of the model: "Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models" in PyTorch☆28Updated this week
- Utilities for Training Very Large Models☆58Updated last year