yuhuixu1993 / qa-loraLinks
Official PyTorch implementation of QA-LoRA
☆145Updated last year
Alternatives and similar repositories for qa-lora
Users that are interested in qa-lora are comparing it to the libraries listed below
Sorting:
- ☆235Updated last year
- For releasing code related to compression methods for transformers, accompanying our publications☆453Updated 11 months ago
- Code for paper: "QuIP: 2-Bit Quantization of Large Language Models With Guarantees"☆392Updated last year
- [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization☆711Updated last year
- [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning☆634Updated last year
- A family of compressed models obtained via pruning and knowledge distillation☆361Updated last month
- The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction☆389Updated last year
- A simple and effective LLM pruning approach.☆827Updated last year
- Official code for ReLoRA from the paper Stack More Layers Differently: High-Rank Training Through Low-Rank Updates☆469Updated last year
- Explorations into some recent techniques surrounding speculative decoding☆295Updated last year
- Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"☆322Updated 9 months ago
- Code for the paper "QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models".☆279Updated 2 years ago
- ☆551Updated last year
- ☆204Updated last year
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆395Updated last year
- ☆128Updated last year
- Multipack distributed sampler for fast padding-free training of LLMs☆202Updated last year
- Simple implementation of Speculative Sampling in NumPy for GPT-2.☆98Updated 2 years ago
- Automated Identification of Redundant Layer Blocks for Pruning in Large Language Models☆258Updated last year
- Official PyTorch implementation of DistiLLM: Towards Streamlined Distillation for Large Language Models (ICML 2024)☆244Updated 9 months ago
- ☆574Updated last year
- PB-LLM: Partially Binarized Large Language Models☆157Updated 2 years ago
- Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".☆854Updated last year
- A repository dedicated to evaluating the performance of quantizied LLaMA3 using various quantization methods..☆197Updated 11 months ago
- [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.☆884Updated 3 weeks ago
- Unofficial implementation for the paper "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆176Updated last year
- The official implementation of the EMNLP 2023 paper LLM-FP4☆219Updated 2 years ago
- GPTQLoRA: Efficient Finetuning of Quantized LLMs with GPTQ☆101Updated 2 years ago
- [ICML'24] Data and code for our paper "Training-Free Long-Context Scaling of Large Language Models"☆447Updated last year
- Implementation of Speculative Sampling as described in "Accelerating Large Language Model Decoding with Speculative Sampling" by Deepmind☆107Updated last year