Added external repos in Examples (#947)

* Added external repos in Examples

* Docs awesome list

Author: TugdualKerjan

examples/awesome-list.md

@@ -0,0 +1,32 @@
+# Awesome List
+
+A curated list of external projects from the community that leverage the Equinox framework to build models using JAX.
+
+Feel free to create a PR to add your own projects so that the community may benefit from as many examples as possible !
+## Advanced (External Repos)
+- **Mistral 7B**: [GitHub](https://github.com/AakashKumarNain/mistral_jax)
+    - Implementation of the Mistral 7B model.
+- **PaLM**: [GitHub](https://github.com/lucidrains/PaLM-jax)
+    - Implementation of the Pathways Language Model (PaLM).
+- **HiFiGAN**: [GitHub](https://github.com/TugdualKerjan/hifigan-jax)
+    - HiFiGAN vocoder using two discriminators to map mel-spectrograms to audio.
+- **nanoGPT**: [GitHub](https://github.com/TugdualKerjan/nanoEQXGPT)
+    - Port of nanoGPT, a minimalist implementation of a Generative Pre-trained Transformer.
+- **VQVAE**: [GitHub](https://github.com/TugdualKerjan/audio-vae-jax)
+    - Implementation of a VQ-VAE (Vector Quantized Variational Autoencoder) for audio generation.
+
+## Projects Based on Equinox
+- **Levanter**: [GitHub](https://github.com/stanford-crfm/levanter)
+    - Deep learning library for training large language models.
+- **Eqxvision**: [GitHub](https://github.com/paganpasta/eqxvision)
+    - Computer vision library built on Equinox, inspired by torchvision.
+- **Haliax**: [GitHub](https://github.com/stanford-crfm/haliax)
+    - Library for distributed multi-dimensional arrays, designed for large-scale machine learning.
+- **Diffrax**: [GitHub](https://github.com/patrick-kidger/diffrax)
+    - Library for numerical differential equation solvers.
+- **Optimistix**: [GitHub](https://github.com/patrick-kidger/optimistix)
+    - Library for nonlinear optimization.
+- **FlowJAX**: [GitHub](https://github.com/danielward27/flowjax?tab=readme-ov-file)
+    - Library for normalizing flows and probabilistic machine learning.
+- **Lineax**: [GitHub](https://github.com/patrick-kidger/lineax)
+    - Library for linear solvers, linear least squares, and eigenvalue solvers.

examples/mistral_7b.md

@@ -103,19 +103,19 @@ nav:
         - Introductory:
             - CNN on MNIST: 'examples/mnist.ipynb'
             - Train RNN: 'examples/train_rnn.ipynb'
-        - Advanced:
-            - Generative score-based diffusion: 'examples/score_based_diffusion.ipynb'
-            - BERT language model: 'examples/bert.ipynb'
-            - U-Net implementation: 'examples/unet.ipynb'
-            - Vision transformer: 'examples/vision_transformer.ipynb'
-            - Image GAN: 'examples/deep_convolutional_gan.ipynb'
-            - Mistral 7B: 'examples/mistral_7b.md'
         - Features:
             - Freezing parameters: 'examples/frozen_layer.ipynb'
             - Compatibility with init-apply libraries: 'examples/init_apply.ipynb'
             - Stateful operations (e.g. BatchNorm): 'examples/stateful.ipynb'
             - Autoparallelism (e.g. multi-GPU): 'examples/parallelism.ipynb'
             - Serialisation (with hyperparameters): 'examples/serialisation.ipynb'
+        - Advanced (Notebooks):
+            - Generative score-based diffusion: 'examples/score_based_diffusion.ipynb'
+            - BERT language model: 'examples/bert.ipynb'
+            - U-Net implementation: 'examples/unet.ipynb'
+            - Vision transformer: 'examples/vision_transformer.ipynb'
+            - Image GAN: 'examples/deep_convolutional_gan.ipynb'
+        - Awesome list: 'awesome-list.md'
     - Basic API:
         - Modules:
             - 'api/module/module.md'