Update model-release-checklist.md (#1660)

Author: julien-c

docs/hub/model-release-checklist.md

@@ -4,16 +4,13 @@ The Hugging Face Hub is the go-to platform for sharing machine learning models.
 
 ## ⏳ Preparing Your Model for Release
 
-### Uploading models
+### Uploading weights
 
-When uploading models to the hub, it's recommended to follow a set best practices:
+When uploading models to the hub, it's recommended to follow a set of best practices:
 
 - push weights to separate model repositories. Example: prefer uploading individual quantizations/precisions in a standalone repo like [this](https://huggingface.co/jameslahm/yolov10n) over all types/versions in one like [this](https://huggingface.co/kadirnar/Yolov10/tree/main).
-- adopt the [Mixin class](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) when pushing custom PyTorch models.
 - leverage [safetensors](https://huggingface.co/docs/safetensors/en/index) for weights serialization as opposed to pickle.
 
-We wrote an extensive guide on uploading best practices [here](models-uploading).
-
 ### Writing a Comprehensive Model Card
 
 A well-crafted model card (the `README.md` file in your repository) is essential for discoverability, reproducibility, and effective sharing. Your model card should include:
@@ -58,6 +55,10 @@ To maximize your model's reach and usability:
 
 You can also [create your own model library](https://huggingface.co/docs/hub/models-adding-libraries) or add Hub support to another existing library or codebase.
 
+Finally, you can adopt the [Mixin class](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) when pushing custom PyTorch models.
+
+We wrote an extensive guide on uploading best practices [here](https://huggingface.co/docs/hub/models-uploading).
+
 Bonus: a recognised library also allows you to track downloads of your model over time.
 
 2. **Pipeline Tag Selection**: Choose the correct [pipeline tag](https://huggingface.co/docs/hub/model-cards#specifying-a-task--pipelinetag-) that accurately reflects your model's primary task. This tag determines how your model appears in search results and which widgets are displayed on your model page.