Fix typos

Author: tolgacangoz

README.md

@@ -35,7 +35,7 @@ More information coming soon!
 If it's not the case yet, you can check these free resources:
 - Python: https://www.udacity.com/course/introduction-to-python--ud1110
 - Intro to Deep Learning with PyTorch: https://www.udacity.com/course/deep-learning-pytorch--ud188
-- PyTorch in 60min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
+- PyTorch in 60 min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
 
 ## FAQ
 **Is this class free?**
@@ -54,11 +54,11 @@ You can create one here 👉 [https://huggingface.co/join](https://huggingface.c
 
 The course will consist of at least **4 Units.** More will be added as time goes on, on topics like diffusion for audio. 
 
-Each unit consists of some theory and background alongisde one or more hands-on notebooks. Some units will also contain suggested projects and we'll have competitions and swag for the best pipelines and demos (more details TDB).
+Each unit consists of some theory and background alongside one or more hands-on notebooks. Some units will also contain suggested projects and we'll have competitions and swag for the best pipelines and demos (more details TDB).
 
 ## 🌎 Languages and translations
 
-Members of the 🤗 community have begin translating the course! We're planning to host this course on the [Hugging Face website](https://huggingface.co/), so if you're interested in contributing a translation, we recommend waiting until we've formatted the English content in it's final form.
+Members of the 🤗 community have begun translating the course! We're planning to host this course on the [Hugging Face website](https://huggingface.co/), so if you're interested in contributing a translation, we recommend waiting until we've formatted the English content in it's final form.
 
 | Language                                                                      | Authors |
 |:------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|

hackathon/README.md

@@ -60,7 +60,7 @@ We will be awarding 3 prizes per theme, where **winners are determined by the mo
 
 * [Hugging Face Pro subscription](https://huggingface.co/pricing) for 1 year or a $100 voucher for the [Hugging Face merch store](https://store.huggingface.co/)
 
-**2nd place winnner**
+**2nd place winner**
 
 * A copy of the [_NLP with Transformers_](https://transformersbook.com/) book or a $50 voucher for the [Hugging Face merch store](https://store.huggingface.co/)
 
@@ -81,9 +81,9 @@ Google Colab will be sponsoring this event by providing fee Colab Pro credits to
 
 ### What data is allowed for fine-tuning?
 
-You can use any images that belong to you or for which a permissive license allows for. If you'd like to submit a model trained on faces (e.g. as a Wilcard submission), we recommend using your own likeness. Ideally, use your own data where you can - we'd love to see your pets or favorite local landscape features, and we suspect the likes and prizes will tend to go to those who do something nice and personal 😁
+You can use any images that belong to you or for which a permissive license allows for. If you'd like to submit a model trained on faces (e.g. as a Wildcard submission), we recommend using your own likeness. Ideally, use your own data where you can - we'd love to see your pets or favorite local landscape features, and we suspect the likes and prizes will tend to go to those who do something nice and personal 😁.
 
-### Are other fine-tuning techniques like textual inversion allowed?
+### Are other fine-tuning techniques like Textual Inversion allowed?
 
-Absolutely! Although this hackathon is focused on DreamBooth, you're welcome (and encouraged) to experiment with other fine-tuning techniques. This also means you can use whatever frameworks, code, or services that help you make delightful models for the community to enjoy 🥰
+Absolutely! Although this hackathon is focused on DreamBooth, you're welcome (and encouraged) to experiment with other fine-tuning techniques. This also means you can use whatever frameworks, code, or services that help you make delightful models for the community to enjoy 🥰.
 

hackathon/dreambooth.ipynb

@@ -59,7 +59,7 @@
     }
    ],
    "source": [
-    "!pip install -q diffusers"
+    "%pip install -q diffusers"
    ]
   },
   {

unit1/02_diffusion_models_from_scratch.ipynb

@@ -7,11 +7,11 @@ models work and how to create your own using the 🤗 Diffusers library.
 
 Here are the steps for this unit:
 
-- Make sure you've [signed up for this course](https://huggingface.us17.list-manage.com/subscribe?u=7f57e683fa28b51bfc493d048&id=ef963b4162) so that you can be notified when new material is released
-- Read through the introductory material below as well as any of the additional resources that sound interesting
-- Check out the _**Introduction to Diffusers**_  notebook below to put theory into practice with the 🤗 Diffusers library
-- Train and share your own diffusion model using the notebook or the linked training script
-- (Optional) Dive deeper with the _**Diffusion Models from Scratch**_ notebook if you're interested in seeing a minimal from-scratch implementation and exploring the different design decisions involved
+- Make sure you've [signed up for this course](https://huggingface.us17.list-manage.com/subscribe?u=7f57e683fa28b51bfc493d048&id=ef963b4162) so that you can be notified when new material is released.
+- Read through the introductory material below as well as any of the additional resources that sound interesting.
+- Check out the _**Introduction to Diffusers**_  notebook below to put theory into practice with the 🤗 Diffusers library.
+- Train and share your own diffusion model using the notebook or the linked training script.
+- (Optional) Dive deeper with the _**Diffusion Models from Scratch**_ notebook if you're interested in seeing a minimal from-scratch implementation and exploring the different design decisions involved.
 - (Optional) Check out [this video](https://www.youtube.com/watch?v=09o5cv6u76c) for an informal run-through the material for this unit.