OscarSavolainen / Quantization-TutorialsLinks
A bunch of coding tutorials for my Youtube videos on Neural Network Quantization.
☆16Updated last year
Alternatives and similar repositories for Quantization-Tutorials
Users that are interested in Quantization-Tutorials are comparing it to the libraries listed below
Sorting:
- TensorRT encapsulation, learn, rewrite, practice.☆28Updated 2 years ago
- 使用 CUDA C++ 实现的 llama 模型推理框架☆57Updated 6 months ago
- 使用 cutlass 实现 flash-attention 精简版,具有教学意义☆41Updated 9 months ago
- ☆23Updated 3 weeks ago
- Some common CUDA kernel implementations (Not the fastest).☆18Updated last month
- ☆24Updated last year
- EasyNN是一个面向教学而开发的神经网络推理框架,旨在让大家0基础也能自主完成推理框架编写!☆28Updated 9 months ago
- 🎓Automatically Update circult-eda-mlsys-tinyml Papers Daily using Github Actions (Update Every 8th hours)☆10Updated this week
- base quantization methods including: QAT, PTQ, per_channel, per_tensor, dorefa, lsq, adaround, omse, Histogram, bias_correction.etc☆45Updated 2 years ago
- 📚FFPA(Split-D): Extend FlashAttention with Split-D for large headdim, O(1) GPU SRAM complexity, 1.8x~3x↑🎉 faster than SDPA EA.☆183Updated 3 weeks ago
- Flash Attention in raw Cuda C beating PyTorch☆22Updated last year
- b站上的课程☆75Updated last year
- 用C++实现一个简单的Transformer模型。 Attention Is All You Need。☆48Updated 4 years ago
- 使用 cutlass 仓库在 ada 架构上实现 fp8 的 flash attention☆68Updated 9 months ago
- 分层解耦的深度学习推理引擎☆73Updated 3 months ago
- llm theoretical performance analysis tools and support params, flops, memory and latency analysis.☆90Updated last week
- ☆19Updated 2 months ago
- async inference for machine learning model☆26Updated 2 years ago
- TensorRT-in-Action 是一个 GitHub 代码库,提供了使用 TensorRT 的代码示例,并有对应 Jupyter Notebook。☆16Updated 2 years ago
- ☆134Updated last year
- ☆11Updated 2 months ago
- 该代码与B站上的视频 https://www.bilibili.com/video/BV18L41197Uz/?spm_id_from=333.788&vd_source=eefa4b6e337f16d87d87c2c357db8ca7 相关联。☆68Updated last year
- ☆21Updated 4 years ago
- ☆29Updated 6 months ago
- ☆33Updated last year
- A light llama-like llm inference framework based on the triton kernel.☆122Updated this week
- hands on model tuning with TVM and profile it on a Mac M1, x86 CPU, and GTX-1080 GPU.☆48Updated last year
- ☆36Updated 7 months ago
- A Toolkit to Help Optimize Large Onnx Model☆158Updated last year
- Performance of the C++ interface of flash attention and flash attention v2 in large language model (LLM) inference scenarios.☆37Updated 3 months ago