Alternatives and similar repositories for mrt5

Users that are interested in mrt5 are comparing it to the libraries listed below

• RobertCsordas / moeut
  ☆91Updated last year
• LAGoM-NLP / transtokenizer
  ☆57Updated last month
• ltgoslo / bert-in-context
  Official implementation of "BERTs are Generative In-Context Learners"
  ☆32Updated 10 months ago
• bminixhofer / zett
  Code for Zero-Shot Tokenizer Transfer
  ☆142Updated last year
• ContextualAI / CLAIR_and_APO
  Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment
  ☆61Updated last year
• facebookresearch / mexma
  MEXMA: Token-level objectives improve sentence representations
  ☆42Updated last year
• epfml / DenseFormer
  ☆82Updated last year
• GenRobo / MatMamba
  Code and pretrained models for the paper: "MatMamba: A Matryoshka State Space Model"
  ☆62Updated last year
• Aleph-Alpha-Research / trigrams
  ☆59Updated 2 months ago
• dmis-lab / Monet
  [ICLR 2025] Monet: Mixture of Monosemantic Experts for Transformers
  ☆75Updated 7 months ago
• kjslag / spacebyte
  A byte-level decoder architecture that matches the performance of tokenized Transformers.
  ☆67Updated last year
• zaydzuhri / flame
  Fork of Flame repo for training of some new stuff in development
  ☆19Updated last month
• TRI-ML / linear_open_lm
  A repository for research on medium sized language models.
  ☆77Updated last year
• devvrit / matformer
  MatFormer repo
  ☆70Updated last year
• catie-aq / flashT5
  A fast implementation of T5/UL2 in PyTorch using Flash Attention
  ☆113Updated 3 months ago
• bminixhofer / tokenkit
  A toolkit implementing advanced methods to transfer models and model knowledge across tokenizers.
  ☆62Updated 7 months ago
• zaydzuhri / softpick-attention
  Landing repository for the paper "Softpick: No Attention Sink, No Massive Activations with Rectified Softmax"
  ☆86Updated 4 months ago
• recursal / GoldFinch-paper
  GoldFinch and other hybrid transformer components
  ☆45Updated last year
• JHU-CLSP / ettin-encoder-vs-decoder
  State-of-the-art paired encoder and decoder models (17M-1B params)
  ☆58Updated 6 months ago
• trapoom555 / Language-Model-STS-CFT
  Improving Text Embedding of Language Models Using Contrastive Fine-tuning
  ☆64Updated last year
• KaiNylund / lm-weights-encode-time
  ☆68Updated last year
• ahstat / episodic-memory-benchmark
  Synthetic data generation and benchmark implementation for "Episodic Memories Generation and Evaluation Benchmark for Large Language Mode…
  ☆63Updated 4 months ago
• OpenEvaByte / evabyte
  EvaByte: Efficient Byte-level Language Models at Scale
  ☆115Updated 9 months ago
• kyegomez / Infini-attention
  Implementation of the paper: "Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention" from Google in pyTO…
  ☆58Updated last week
• RWKV / RWKV-LM
  RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best…
  ☆59Updated 10 months ago
• ltgoslo / gpt-bert
  Official implementation of "GPT or BERT: why not both?"
  ☆61Updated 6 months ago
• vmarinowski / infini-attention
  An unofficial pytorch implementation of 'Efficient Infinite Context Transformers with Infini-attention'
  ☆54Updated last year
• sanyalsunny111 / LLM-Inheritune
  [TMLR 2026] When Attention Collapses: How Degenerate Layers in LLMs Enable Smaller, Stronger Models
  ☆122Updated last year
• epfml / schedules-and-scaling
  Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"
  ☆89Updated last year
• wolfecameron / lora_instruction_tune
  ☆37Updated last year