hao-ai-lab / LookaheadDecodingLinks
[ICML 2024] Break the Sequential Dependency of LLM Inference Using Lookahead Decoding
☆1,270Updated 5 months ago
Alternatives and similar repositories for LookaheadDecoding
Users that are interested in LookaheadDecoding are comparing it to the libraries listed below
Sorting:
- Official Implementation of EAGLE-1 (ICML'24), EAGLE-2 (EMNLP'24), and EAGLE-3.☆1,462Updated last week
- Memory optimization and training recipes to extrapolate language models' context length to 1 million tokens, with minimal hardware.☆739Updated 10 months ago
- Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads☆2,593Updated last year
- Serving multiple LoRA finetuned LLM as one☆1,082Updated last year
- [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning☆629Updated last year
- Large Context Attention☆724Updated 6 months ago
- YaRN: Efficient Context Window Extension of Large Language Models☆1,575Updated last year
- Microsoft Automatic Mixed Precision Library☆616Updated 10 months ago
- Scalable toolkit for efficient model alignment☆835Updated 2 weeks ago
- [NeurIPS'24 Spotlight, ICLR'25, ICML'25] To speed up Long-context LLMs' inference, approximate and dynamic sparse calculate the attention…☆1,098Updated this week
- A family of open-sourced Mixture-of-Experts (MoE) Large Language Models☆1,577Updated last year
- Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".☆824Updated 11 months ago
- distributed trainer for LLMs☆578Updated last year
- S-LoRA: Serving Thousands of Concurrent LoRA Adapters☆1,846Updated last year
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆875Updated 11 months ago
- A simple and effective LLM pruning approach.☆787Updated last year
- Minimalistic large language model 3D-parallelism training☆2,121Updated last month
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,471Updated last year
- Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".☆2,161Updated last year
- [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.☆838Updated 2 months ago
- Automatically split your PyTorch models on multiple GPUs for training & inference☆658Updated last year
- ☆559Updated 11 months ago
- For releasing code related to compression methods for transformers, accompanying our publications☆438Updated 6 months ago
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.☆2,045Updated last month
- Ring attention implementation with flash attention☆836Updated last week
- [NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support Llama-3/3.1, Llama-2, LLaMA, BLOOM, Vicuna, Baich…☆1,052Updated 10 months ago
- [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization☆701Updated last year
- Fast inference from large lauguage models via speculative decoding☆799Updated 11 months ago
- Ongoing research training transformer language models at scale, including: BERT & GPT-2☆1,406Updated last year
- ☆546Updated 7 months ago