NVlabs / MinitronLinks
A family of compressed models obtained via pruning and knowledge distillation
☆357Updated last month
Alternatives and similar repositories for Minitron
Users that are interested in Minitron are comparing it to the libraries listed below
Sorting:
- For releasing code related to compression methods for transformers, accompanying our publications☆452Updated 10 months ago
- Official PyTorch implementation of QA-LoRA☆145Updated last year
- ☆235Updated last year
- Code for "LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding", ACL 2024☆349Updated 7 months ago
- Unofficial implementation for the paper "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆175Updated last year
- Efficient LLM Inference over Long Sequences☆392Updated 5 months ago
- [ICLR 2025] DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads☆507Updated 9 months ago
- Automated Identification of Redundant Layer Blocks for Pruning in Large Language Models☆256Updated last year
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆391Updated last year
- [ACL 2025 Main] EfficientQAT: Efficient Quantization-Aware Training for Large Language Models☆316Updated last week
- Official PyTorch implementation of DistiLLM: Towards Streamlined Distillation for Large Language Models (ICML 2024)☆240Updated 8 months ago
- Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients.☆202Updated last year
- The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction☆389Updated last year
- [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning☆632Updated last year
- A repository dedicated to evaluating the performance of quantizied LLaMA3 using various quantization methods..☆197Updated 10 months ago
- ☆204Updated last year
- Explorations into some recent techniques surrounding speculative decoding☆295Updated 11 months ago
- [ICML'24] Data and code for our paper "Training-Free Long-Context Scaling of Large Language Models"☆443Updated last year
- Unofficial PyTorch/🤗Transformers(Gemma/Llama3) implementation of Leave No Context Behind: Efficient Infinite Context Transformers with I…☆373Updated last year
- [NeurIPS 24 Spotlight] MaskLLM: Learnable Semi-structured Sparsity for Large Language Models☆181Updated 11 months ago
- Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"☆323Updated 9 months ago
- LongRoPE is a novel method that can extends the context window of pre-trained LLMs to an impressive 2048k tokens.☆273Updated last month
- Implementation of the LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens Paper☆152Updated last year
- Code for paper: "QuIP: 2-Bit Quantization of Large Language Models With Guarantees"☆390Updated last year
- Code repo for the paper "SpinQuant LLM quantization with learned rotations"☆352Updated 9 months ago
- Memory layers use a trainable key-value lookup mechanism to add extra parameters to a model without increasing FLOPs. Conceptually, spars…☆360Updated 11 months ago
- The official implementation of the paper "What Matters in Transformers? Not All Attention is Needed".☆181Updated 3 weeks ago
- ☆128Updated last year
- PyTorch implementation of Infini-Transformer from "Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention…☆294Updated last year
- Repo for Rho-1: Token-level Data Selection & Selective Pretraining of LLMs.☆448Updated last year