Alternatives and similar repositories for EETQ

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

• neuralmagic / AutoFP8
  ☆195Updated 3 months ago
• neuralmagic / nm-vllm
  A high-throughput and memory-efficient inference and serving engine for LLMs
  ☆266Updated 10 months ago
• triton-inference-server / vllm_backend
  ☆291Updated 3 weeks ago
• anyscale / llm-continuous-batching-benchmarks
  ☆120Updated last year
• huggingface / optimum-benchmark
  🏋️ A unified multi-backend utility for benchmarking Transformers, Timm, PEFT, Diffusers and Sentence-Transformers with full support of O…
  ☆310Updated this week
• wejoncy / QLLM
  A general 2-8 bits quantization toolbox with GPTQ/AWQ/HQQ/VPTQ, and export to onnx/onnx-runtime easily.
  ☆177Updated 4 months ago
• SqueezeBits / QUICK
  QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference
  ☆119Updated last year
• jaymody / speculative-sampling
  Simple implementation of Speculative Sampling in NumPy for GPT-2.
  ☆95Updated 2 years ago
• SqueezeAILab / KVQuant
  [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
  ☆372Updated last year
• fpgaminer / GPTQ-triton
  GPTQ inference Triton kernel
  ☆306Updated 2 years ago
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆80Updated 11 months ago
• IsaacRe / vllm-kvcompress
  KV cache compression for high-throughput LLM inference
  ☆134Updated 6 months ago
• neuralmagic / compressed-tensors
  A safetensors extension to efficiently store sparse quantized tensors on disk
  ☆153Updated this week
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆208Updated last week
• nbasyl / LLM-FP4
  The official implementation of the EMNLP 2023 paper LLM-FP4
  ☆212Updated last year
• NVlabs / Minitron
  A family of compressed models obtained via pruning and knowledge distillation
  ☆348Updated 9 months ago
• Cornell-RelaxML / QuIP
  Code for paper: "QuIP: 2-Bit Quantization of Large Language Models With Guarantees"
  ☆377Updated last year
• mlc-ai / llm-perf-bench
  ☆119Updated last year
• npuichigo / openai_trtllm
  OpenAI compatible API for TensorRT LLM triton backend
  ☆214Updated last year
• foundation-model-stack / fms-fsdp
  🚀 Efficiently (pre)training foundation models with native PyTorch features, including FSDP for training and SDPA implementation of Flash…
  ☆261Updated last month
• fw-ai / benchmark
  Benchmark suite for LLMs from Fireworks.ai
  ☆80Updated 3 weeks ago
• AniZpZ / AutoSmoothQuant
  An easy-to-use package for implementing SmoothQuant for LLMs
  ☆104Updated 4 months ago
• microsoft / TransformerCompression
  For releasing code related to compression methods for transformers, accompanying our publications
  ☆440Updated 7 months ago
• mobiusml / gemlite
  Fast low-bit matmul kernels in Triton
  ☆353Updated last week
• efeslab / Atom
  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
  ☆319Updated last year
• usyd-fsalab / fp6_llm
  An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).
  ☆261Updated last month
• snowflakedb / ArcticTraining
  ArcticTraining is a framework designed to simplify and accelerate the post-training process for large language models (LLMs)
  ☆201Updated this week
• IST-DASLab / marlin
  FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.
  ☆886Updated 11 months ago
• SqueezeAILab / SqueezeLLM
  [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
  ☆703Updated last year
• shreyansh26 / Speculative-Sampling
  Implementation of Speculative Sampling as described in "Accelerating Large Language Model Decoding with Speculative Sampling" by Deepmind
  ☆99Updated last year