Github repo help

[collingrichey]

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i am trying to upload a project to github and make it a repo. The issue I keep running into is there is a file too large. Also, something that I want to do for the project is have my folders carry over, but I have not been able to figure it out.

This is project I want to make a repo. Please any info would help.

[WattoX00]

if you have your github account connected to your git just do these from the projects root:
git init
git add .
git commit -m "initial commit"
git branch -M main
git remote add origin https://github.com/YOURNAME/REPO.git
git push -u origin main

about your large files, just remove them if they are not necessary. (just add them into a .gitignore file so they dont upload to github)

If you want to push them too try to pack up the files...

[parthhanda]

It looks like you’re very close — the structure of your project is already fine. The issues you mentioned (large file error and folders not carrying over) are pretty common when pushing a repo for the first time. Here are a few suggestions from my side that might help.

1. Folder structure in GitHub

Git actually tracks files, not empty folders. So if a folder has no tracked files, it won’t appear on GitHub.

Fix:

• Make sure each folder has at least one file in it.
• If you want to keep an empty folder, add a placeholder file like:

models/.gitkeep
data/.gitkeep

This forces Git to include the folder in the repo.

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2. Large file issue

GitHub normally blocks files larger than 100MB. If your dataset or model files are big (which is common in ML projects), you have a few options.

Option A — Use .gitignore

Usually datasets and generated files shouldn’t be pushed.

Example .gitignore:

kaggle-data/
data/*.csv
data/*.zip
*.pkl
*.model

This keeps your repo clean and lightweight.

---

Option B — Use Git LFS (Best for models or large assets)

If you actually need the large files in the repo:

git lfs install
git lfs track "*.pkl"
git lfs track "*.model"
git add .gitattributes
git add .
git commit -m "track large files with git lfs"
git push

Git LFS stores large files separately but keeps them linked to the repo.

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3. Good practice for ML projects

Instead of uploading datasets, many repos do this:

• Keep only code and configs in the repo
• Add instructions in README.md on how to download the dataset

Example:

## Dataset

Download the dataset from Kaggle:
https://kaggle.com/...

Place it inside:
data/

This makes the repo much cleaner.

---

4. Example of a clean repo structure

project/

├── data/
│   └── .gitkeep
├── models/
│   └── .gitkeep
├── bracket_sim.py
├── data_scraper.py
├── prediction_model.py
├── README.md
├── .gitignore
└── LICENSE

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5. One more small tip

If Git already tried to push a large file and failed, remove it from tracking first:

git rm --cached path/to/largefile
git commit -m "remove large file"
git push

---

Hope this helps — your project structure already looks solid, so you're mostly just dealing with a few common GitHub setup issues.