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Open source platform for the machine learning lifecycle
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
A algebraic word problem dataset, with multiple choice questions annotated with rationales.
Instruct-tune LLaMA on consumer hardware
Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"
A curated list for Efficient Large Language Models
π€ PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
[TMLR 2024] Efficient Large Language Models: A Survey
π©βπ»π¨βπ» AI μμ§λμ΄ κΈ°μ λ©΄μ μ€ν°λ (βοΈ 1k+)
Sea-Snell / JAX_llama
Forked from meta-llama/llamaInference code for LLaMA models in JAX
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
tiktoken is a fast BPE tokeniser for use with OpenAI's models.
An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
PyTorch extensions for high performance and large scale training.
Implementation of Rotary Embeddings, from the Roformer paper, in Pytorch
A modern model graph visualizer and debugger
Code Transformer neural network components piece by piece
Google Research
[ACL'20] HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.
Datasets, Transforms and Models specific to Computer Vision
Ongoing research training transformer models at scale
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Everything you want to know about Google Cloud TPU