add installation section to readme

Author: Essoz

README.md

@@ -4,8 +4,6 @@
 </picture>
 <h1>TrainCheck: Invariant Checking & Observability for AI Training</h1>
 
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-[![format and types](https://github.com/OrderLab/traincheck/actions/workflows/correctness_checks.yml/badge.svg)](https://github.com/OrderLab/traincheck/actions/workflows/correctness_checks.yml)
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@@ -31,6 +29,16 @@ No manual tests required. TrainCheck automatically learns the invariants of your
 Drop-in support for PyTorch, Hugging Face, and industry-class workloads using DeepSpeed/Megatron and more.
 
 ---
+## Installation
+
+Install TrainCheck in the Python environment where you will run your training script:
+
+```bash
+pip3 install traincheck
+```
+
+For detailed setup (CUDA configuration, UV, conda environments), see the [Installation Guide](https://orderlab.io/TrainCheck/installation-guide/).
+
 
 ### How It Works
 
@@ -49,14 +57,13 @@ Work through [5‑Minute Experience with TrainCheck](./docs/5-min-tutorial.md).
 
 ## Documentation
 
-- **[Installation Guide](./docs/installation-guide.md)**
-- **[Usage Guide: Scenarios and Limitations](./docs/usage-guide.md)**
-- **[TrainCheck Technical Doc](./docs/technical-doc.md)**
-- **[TrainCheck Dev RoadMap](./ROADMAP.md)**
+- **[Installation Guide](https://orderlab.io/TrainCheck/installation-guide/)**
+- **[Usage Guide: Scenarios and Limitations](https://orderlab.io/TrainCheck/usage-guide/)**
+- **[TrainCheck Technical Doc](https://orderlab.io/TrainCheck/technical-doc/)**
 
 ## Status
 
-TrainCheck is under active development. Please join our 💬 [Discord server](https://discord.gg/VwxpJDvB) or file a GitHub issue for support. 
+TrainCheck is under active development. Please join our 💬 [Discord server](https://discord.gg/VwxpJDvB) or file a GitHub issue for support. You can also reach the team at [traincheck@umich.edu](mailto:traincheck@umich.edu).
 We welcome feedback and contributions from early adopters.
 
 ## Contributing

docs/installation-guide.md

@@ -1,3 +1,21 @@
+## Quick Install
+
+Install TrainCheck in the Python environment where you will run your training script:
+
+```bash
+pip3 install traincheck
+```
+
+> **Note:** Install PyTorch separately first (see step 3 below) to ensure the right CUDA version is selected. If you already have PyTorch installed, the command above is all you need.
+
+For UV users:
+
+```bash
+uv pip install traincheck
+```
+
+---
+
 ## Compatibility
 
 - **Python**: 3.10+ (due to reliance on type annotations)
@@ -47,7 +65,12 @@
     conda install cudatoolkit
     ```
 
-5. **Clone & install TrainCheck**
+5. **Install TrainCheck**
+    ```bash
+    pip3 install traincheck
+    ```
+
+    If you prefer to install from source:
     ```bash
     git clone https://github.com/OrderLab/TrainCheck.git
     cd TrainCheck

pyproject.toml

@@ -12,7 +12,7 @@ include = ["traincheck", "traincheck.*"]
 [project]
 requires-python = ">= 3.10"
 name = "traincheck"
-version = "0.1.0"
+version = "0.1.2"
 description = "Training with Confidence: Catching Silent DL Training Bugs with Automated Proactive Checks"
 authors = [
   { name = "Yuxuan Jiang", email = "jyuxuan@umich.edu" },