Pinned Repositories
accelerate
🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
AutoAWQ
AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:
bitsandbytes
Accessible large language models via k-bit quantization for PyTorch.
ClipBERT
[CVPR 2021 Best Student Paper Honorable Mention, Oral] Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks.
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
Diffusion-MU-Attack
The official implementation of the paper "To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now". This work introduces one fast and efficient attack methods to generate toxic content for safety-driven diffusion models.
FlexFlow
A distributed deep learning framework.
GEAR
GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM
intel-extension-for-transformers
Extending Hugging Face transformers APIs for Transformer-based models and improve the productivity of inference deployment. With extremely compressed models, the toolkit can greatly improve the inference efficiency on Intel platforms.
jiqing-feng's Repositories
jiqing-feng/accelerate
🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
jiqing-feng/AutoAWQ
AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:
jiqing-feng/bitsandbytes
Accessible large language models via k-bit quantization for PyTorch.
jiqing-feng/ClipBERT
[CVPR 2021 Best Student Paper Honorable Mention, Oral] Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks.
jiqing-feng/DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
jiqing-feng/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
jiqing-feng/Diffusion-MU-Attack
The official implementation of the paper "To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now". This work introduces one fast and efficient attack methods to generate toxic content for safety-driven diffusion models.
jiqing-feng/FlexFlow
A distributed deep learning framework.
jiqing-feng/GEAR
GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM
jiqing-feng/intel-extension-for-transformers
Extending Hugging Face transformers APIs for Transformer-based models and improve the productivity of inference deployment. With extremely compressed models, the toolkit can greatly improve the inference efficiency on Intel platforms.
jiqing-feng/lm-evaluation-harness
A framework for few-shot evaluation of autoregressive language models.
jiqing-feng/LookaheadDecoding
jiqing-feng/neural-compressor
Intel® Neural Compressor (formerly known as Intel® Low Precision Optimization Tool), targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
jiqing-feng/optimum
🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools
jiqing-feng/optimum-intel
Accelerate inference of 🤗 Transformers with Intel optimization tools
jiqing-feng/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
jiqing-feng/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
jiqing-feng/pytorch_geometric
Graph Neural Network Library for PyTorch
jiqing-feng/tau
Pipeline Parallelism for PyTorch
jiqing-feng/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
jiqing-feng/Lora
jiqing-feng/models
Intel® AI Reference Models: contains Intel optimizations for running deep learning workloads on Intel® Xeon® Scalable processors and Intel® Data Center GPUs
jiqing-feng/ProtST
Camera-ready repo for ProtST
jiqing-feng/q-diffusion
[ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.
jiqing-feng/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs