BlackSamorez / tensor_parallelLinks
Automatically split your PyTorch models on multiple GPUs for training & inference
☆654Updated last year
Alternatives and similar repositories for tensor_parallel
Users that are interested in tensor_parallel are comparing it to the libraries listed below
Sorting:
- [ICML 2024] Break the Sequential Dependency of LLM Inference Using Lookahead Decoding☆1,251Updated 3 months ago
- Pipeline Parallelism for PyTorch☆767Updated 9 months ago
- [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning☆612Updated last year
- [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization☆689Updated 9 months ago
- Ongoing research training transformer language models at scale, including: BERT & GPT-2☆1,394Updated last year
- distributed trainer for LLMs☆575Updated last year
- Large Context Attention☆714Updated 4 months ago
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆831Updated 9 months ago
- Fast Inference Solutions for BLOOM☆564Updated 7 months ago
- Microsoft Automatic Mixed Precision Library☆602Updated 8 months ago
- Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".☆803Updated 9 months ago
- Official code for ReLoRA from the paper Stack More Layers Differently: High-Rank Training Through Low-Rank Updates☆456Updated last year
- train llama on a single A100 80G node using 🤗 transformers and 🚀 Deepspeed Pipeline Parallelism☆220Updated last year
- Ring attention implementation with flash attention☆774Updated 2 weeks ago
- Implementation of 💍 Ring Attention, from Liu et al. at Berkeley AI, in Pytorch☆514Updated 3 weeks ago
- Scalable toolkit for efficient model alignment☆807Updated this week
- ☆543Updated 5 months ago
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,417Updated 10 months ago
- LOMO: LOw-Memory Optimization☆986Updated 11 months ago
- Official repository of NEFTune: Noisy Embeddings Improves Instruction Finetuning☆396Updated last year
- Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".☆2,123Updated last year
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆357Updated 9 months ago
- A simple and effective LLM pruning approach.☆756Updated 9 months ago
- Official PyTorch implementation of QA-LoRA☆137Updated last year
- Memory optimization and training recipes to extrapolate language models' context length to 1 million tokens, with minimal hardware.☆727Updated 8 months ago
- Pytorch implementation of DoReMi, a method for optimizing the data mixture weights in language modeling datasets☆328Updated last year
- Code for the ALiBi method for transformer language models (ICLR 2022)☆530Updated last year
- [NeurIPS'23] H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.☆448Updated 10 months ago
- Explorations into some recent techniques surrounding speculative decoding☆268Updated 5 months ago
- Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"☆287Updated 3 months ago