Update HFSummaryWriter snippet for a diff

src/index.md

@@ -152,13 +152,21 @@ Plot.plot({
 
 The Tensorboard traces can also easily be uploaded to the Hub using the [huggingface_hub](https://huggingface.co/docs/huggingface_hub/package_reference/tensorboard) library, if you don't rely on Transformers. All it takes is to use the `HFSummaryWriter` class and its methods to append data:
 
-```py
-from huggingface_hub import HFSummaryWriter
+```diff
+# Taken from https://pytorch.org/docs/stable/tensorboard.html
+- from torch.utils.tensorboard import SummaryWriter
++ from huggingface_hub import HFSummaryWriter
+
+import numpy as np
+
+- writer = SummaryWriter()
++ writer = HFSummaryWriter(repo_id="username/my-trained-model")
 
-# Logs are automatically pushed every 5 minutes (default) + when exiting the context manager
-with HFSummaryWriter(repo_id="test_hf_logger") as logger:
-    logger.add_scalar("a", 1)
-    logger.add_scalar("b", 2)
+for n_iter in range(100):
+    writer.add_scalar('Loss/train', np.random.random(), n_iter)
+    writer.add_scalar('Loss/test', np.random.random(), n_iter)
+    writer.add_scalar('Accuracy/train', np.random.random(), n_iter)
+    writer.add_scalar('Accuracy/test', np.random.random(), n_iter)
 ```
 
 This logger was added in June 2023 in the [v0.16.2](https://github.com/huggingface/huggingface_hub/releases/tag/v0.16.2) version of the library and is a good alternative for those who don't use Transformers. Its usage is still confidential. Feel free to try it and report if it helps you generate training metrics!