cavedave · alexandercronin · Aug 19, 2025
diff --git a/Notes.txt b/Notes.txt
@@ -14,4 +14,14 @@ Images
 - reduce the size of the `load your key into secrets` image as it take a large portion of a page
 
 This sentence is unclear
-- But you don't consider getting your brain to learn the difference between a good/bad/urgent/valuable  invoice/request/email/sales lead training a model.
+- But you don't consider getting your brain to learn the difference between a good/bad/urgent/valuable  invoice/request/email/sales lead training a model.
+
+
+# Added 2025.08.19
+Training Times 
+Linux
+- Dell i7 64GB no GPU training time = 38 mins
+- MacBook Pro M1 training time = 13 mins
+
+ReadMe 
+- Updated in detail, please review and verify it is correct. 
diff --git a/README.md b/README.md
@@ -18,90 +18,135 @@ This project shows you how to take an idea ("I want to classify emails automatic
 
 ### 1. Clone and Setup
 
+#### 1.1 Mac OSX / Linux 
 
-In Mac osx
-```bash
-
-# 1) Install uv (one time). If you already have python you are happy with skip this step and make a folder
-# macOS/Linux:
-#curl -LsSf https://astral.sh/uv/install.sh | sh
-
+##### 1.1.1 Install uv (one time) 
+If you already have python you are happy with skip this step and make a folder
+```
+# curl -LsSf https://astral.sh/uv/install.sh | sh
+uv --version
+```
+#####  1.2.2 Download project repository
+```
+git --version
 git clone https://github.com/cavedave/ai-email-classifier.git
-# 2) Project folder
+```
+Change directory in to the downloaded repo to verify it has succeeded
+```
 cd ai-email-classifier
+ls
+```
+###### 1.2.3 Create and activate virtual environment
+```
 uv venv --python 3.13 venv
-# 3) Activate virtual environment
 source venv/bin/activate  # On Windows: venv\Scripts\activate
+```
+#####  1.2.4  GPU Set Up
+Not typically required
 
-
-# 3) Create env + install deps (very fast)
+##### 1.2.4 Install deps (very fast)
+```
 uv pip install -U pip
 uv pip install jupyterlab ipykernel pandas scikit-learn matplotlib tqdm \
                transformers accelerate huggingface_hub \
                torch \
                google-genai ipywidgets seaborn datasets               
-
-
-
 ```
 
-in windows is a bit of work
-
-First off find what GPU you have.
-```bash
-
-# 0) (One time) Install uv
-irm https://astral.sh/uv/install.ps1 | iex
+#### 1.2 Windows
+In windows is a bit of work
 
+If you may need to install https://aka.ms/vs/17/release/vc_redist.x64.exe from
+https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170
 
+The following command should be executed in powershell
+
+#####  1.2.1 Install uv (one time) 
+If you already have python you are happy with skip this step and make a folder
+```
+# irm https://astral.sh/uv/install.ps1 | iex
+uv --version
+```
 Find where uv is installed and write it down 
-# Find uv.exe
+Find uv.exe
+
+```
 Get-ChildItem -Recurse $env:USERPROFILE -Filter uv.exe -ErrorAction SilentlyContinue
+```
+Expected output:`C:\Users\<username>\.local\bin`
 
-this will output something like 
-$uvBin = 'C:\Users\reall\.local\bin'
-#double check its thereß
+Create a variable to reference location
+```
+$uvBin = 'C:\Users\<username>\.local\bin' `
+```
+Double check `uv` is there
+```
 if (-not (Test-Path "$uvBin\uv.exe")) {
   Write-Error "uv.exe not found in $uvBin"; exit 1
 }
-
-# Add to PATH for current session if missing
+```
+Add `uv` to PATH for current session if missing
+```
 if (-not ($env:Path -split ';' | Where-Object { $_ -ieq $uvBin })) {
   $env:Path = "$uvBin;$env:Path"
 }
+```
+Verify that the $uvBin path is in your system path 
+```
+echo $env:Path
+```
+Open a new terminal and ensure `uv` can be found 
+```dotnetcli
+uv --version 
+```
 
-# 1) Get the project
+#####  1.2.2 Download project repository
+
+```
+git --version
 git clone https://github.com/cavedave/ai-email-classifier.git
-cd ai-email-classifier
+```
 
-##if git doesnt work 
+If if `git` is not on your machine you can get the project using `curl` 
 
+Option 1 - use curl & tar
+```dotnetcli
+C:\Windows\System32\curl.exe -L -o ai-email-classifier.zip https://github.com/cavedave/ai-email-classifier/archive/refs/heads/main.zip
+tar -xf tar -xf ai-email-classifier.zip
+```
+Option 2 - use the default windows options
+```
+Invoke-WebRequest -Uri https://github.com/cavedave/ai-email-classifier/archive/refs/heads/main.zip -OutFile ai-email-classifier.zip
+Expand-Archive -Path ai-email-classifier.zip -DestinationPath .
+```
 
-# Verify
-git --version
+Change directory in to the downloaded repo to verify it has succeeded
+```
+cd ai-email-classifier-main
+ls
+```
 
-# 2) Create & activate a Python 3.12 virtual env
+#####  1.2.3 Create and activate virtual environment
+```
 uv venv --python 3.12 venv
 .\venv\Scripts\Activate.ps1
+```
+#####  1.2.4  GPU Set Up
 
-Find your driver as in cuda126 is assume dbelow 
-# Pick ONE that matches your driver (example uses CUDA 12.6):
+Find what GPU you have.
+```bash
+wmic path win32_videocontroller get name
+```
+Find your driver as in cuda126 is assumed below 
+Pick ONE that matches your driver (example uses CUDA 12.6):
+```
 uv pip install --index-url https://download.pytorch.org/whl/cu126 torch torchvision torchaudio
-# 3) Install deps (CPU)
-uv pip install -U pip
-uv pip install jupyterlab ipykernel pandas scikit-learn matplotlib tqdm  transformers accelerate huggingface_hub torch google-genai ipywidgets seaborn datasets
-
-
-
 ```
-If you dont have git download the source this way
-```bash
 
-
-curl -L -o ai-email-classifier.zip \
-  https://github.com/cavedave/ai-email-classifier/archive/refs/heads/main.zip
-unzip ai-email-classifier.zip
-cd ai-email-classifier-main
+#####  1.2.5  Install deps (CPU)
+```
+uv pip install -U pip
+uv pip install jupyterlab ipykernel pandas scikit-learn matplotlib tqdm transformers accelerate huggingface_hub torch google-genai ipywidgets seaborn datasets
 ```
 
 ### 2. Launch Jupyter Lab
@@ -127,14 +172,11 @@ Navigate to `notebooks/train_bert_model_CLEAN.ipynb` and run the cells to:
 
 ## Learning Path
 
-
 ## Key Technologies
 
 - **Python +**
 - **Transformers (Hugging Face)**: BERT model implementation
 - **PyTorch**: Deep learning framework
-
-
 - **Pandas**: Data manipulation
 
 
@@ -162,8 +204,32 @@ MIT License - feel free to use this for your own projects!
 ## Next Steps
 
 Ready to build your own AI tool? Start with:
-1. **Understand the architecture** in `docs/`
-2. **Follow the training tutorial** in the notebook
+1. **Understand the architecture** in `docs/` 
+2. **Follow the training tutorial** in the notebookjupyter lab
 3. **Customize for your domain**
 4. **Deploy and iterate!**
 
+# Known Issues
+
+## Windows install
+
+### Error 1
+```dotnetcli
+...
+OSError: [WinError 126] The specified module could not be found. Error loading "C:\Users\vboxuser\Desktop\ai-email-classifier-main\venv\Lib\site-packages\torch\lib\c10.dll" or one of its dependencies.
+```
+#### Solution: 
+Install Microsoft Visual C++ Redistributable by the link provided at the top of the error, The link below provides more information
+Install https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170
+
+### Error 2
+```dotnetcli
+...
+ImportError: cannot import name 'GenerationMixin' from 'transformers.generation' (C:\Users\vboxuser\Desktop\ai-email-classifier-main\venv\Lib\site-packages\transformers\generation\__init__.py)
+```
+##### Solution
+```dotnetcli
+pip uninstall transformers torch
+pip install transformers torch
+```
+Alternatively delete and recreate virtual environment