update README

Author: lmxyy

.github/ISSUE_TEMPLATE/1-bug-report.yml

@@ -8,7 +8,7 @@ body:
     attributes:
       label: Checklist
       options:
-        - label: 1. I have searched for related issues and FAQs (https://github.com/mit-han-lab/nunchaku/blob/main/docs/faq.md) but was unable to find a solution.
+        - label: 1. I have searched for related issues and FAQs (https://nunchaku.tech/docs/nunchaku/faq/faq.html) but was unable to find a solution.
         - label: 2. The issue persists in the latest version.
         - label: 3. Please note that without environment information and a minimal reproducible example, it will be difficult for us to reproduce and address the issue, which may delay our response.
         - label: 4. If your report is a question rather than a bug, please submit it as a discussion at https://github.com/mit-han-lab/nunchaku/discussions/new/choose. Otherwise, this issue will be closed.

.github/pull_request_template.md

@@ -11,8 +11,8 @@
 ## Checklist
 
 - [ ] Code is formatted using Pre-Commit hooks.
-- [ ] Relevant unit tests are added in the [`tests`](../tests) directory following the guidance in [`tests/README.md`](../tests/README.md).
-- [ ] [README](../README.md) and example scripts in [`examples`](../examples) are updated if necessary.
+- [ ] Relevant unit tests are added in the [`tests`](../tests) directory following the guidance in [`Contribution Guide`](https://nunchaku.tech/docs/nunchaku/developer/contribution_guide.html).
+- [ ] [Documentation](../docs/source) and example scripts in [`examples`](../examples) are updated if necessary.
 - [ ] Throughput/latency benchmarks and quality evaluations are included where applicable.
 - [ ] **For reviewers:** If you're only helping merge the main branch and haven't contributed code to this PR, please remove yourself as a co-author when merging.
 - [ ] Please feel free to join our [Slack](https://join.slack.com/t/nunchaku/shared_invite/zt-3170agzoz-NgZzWaTrEj~n2KEV3Hpl5Q), [Discord](https://discord.gg/Wk6PnwX9Sm) or [WeChat](https://github.com/mit-han-lab/nunchaku/blob/main/assets/wechat.jpg) to discuss your PR.

README.md

@@ -40,7 +40,7 @@ Join our user groups on [**Slack**](https://join.slack.com/t/nunchaku/shared_inv
 ## Overview
 
 ![teaser](https://huggingface.co/mit-han-lab/nunchaku-artifacts/resolve/main/nunchaku/assets/teaser.jpg)
-SVDQuant is a post-training quantization technique for 4-bit weights and activations that well maintains visual fidelity. On 12B FLUX.1-dev, it achieves 3.6× memory reduction compared to the BF16 model. By eliminating CPU offloading, it offers 8.7× speedup over the 16-bit model when on a 16GB laptop 4090 GPU, 3× faster than the NF4 W4A16 baseline. On PixArt-∑, it demonstrates significantly superior visual quality over other W4A4 or even W4A8 baselines. "E2E" means the end-to-end latency including the text encoder and VAE decoder.
+**Nunchaku** is a high-performance inference engine for low-bit neural networks. It implements **SVDQuant**, a post-training quantization technique for 4-bit weights and activations that well maintains visual fidelity. On 12B FLUX.1-dev, it achieves 3.6× memory reduction compared to the BF16 model. By eliminating CPU offloading, it offers 8.7× speedup over the 16-bit model when on a 16GB laptop 4090 GPU, 3× faster than the NF4 W4A16 baseline. On PixArt-∑, it demonstrates significantly superior visual quality over other W4A4 or even W4A8 baselines. "E2E" means the end-to-end latency including the text encoder and VAE decoder.
 
 **SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models**<br>
 [Muyang Li](https://lmxyy.me)\*, [Yujun Lin](https://yujunlin.com)\*, [Zhekai Zhang](https://hanlab.mit.edu/team/zhekai-zhang)\*, [Tianle Cai](https://www.tianle.website/#/), [Xiuyu Li](https://xiuyuli.com), [Junxian Guo](https://github.com/JerryGJX), [Enze Xie](https://xieenze.github.io), [Chenlin Meng](https://cs.stanford.edu/~chenlin/), [Jun-Yan Zhu](https://www.cs.cmu.edu/~junyanz/), and [Song Han](https://hanlab.mit.edu/songhan) <br>