GPT4All Updated Docs and FAQ (#632)

* working on docs

* more doc organization

* faq

* some reformatting

gpt4all-bindings/python/docs/gpt4all_python.md

@@ -1,6 +1,37 @@
 # GPT4All Python API
-The `GPT4All` provides a universal API to call all GPT4All models and 
-introduces additional helpful functionality such as downloading models.
+The `GPT4All` package provides Python bindings and an API to our C/C++ model backend libraries.
+The source code, README, and local build instructions can be found [here](https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/python).
+
+
+## Quickstart
+
+```bash
+pip install gpt4all
+```
+
+In Python, run the following commands to retrieve a GPT4All model and generate a response
+to a prompt.
+
+**Download Note:**
+By default, models are stored in `~/.cache/gpt4all/` (you can change this with `model_path`). If the file already exists, model download will be skipped.
+
+```python
+import gpt4all
+gptj = gpt4all.GPT4All("ggml-gpt4all-j-v1.3-groovy")
+messages = [{"role": "user", "content": "Name 3 colors"}]
+gptj.chat_completion(messages)
+```
+
+## Give it a try!
+[Google Colab Tutorial](https://colab.research.google.com/drive/1QRFHV5lj1Kb7_tGZZGZ-E6BfX6izpeMI?usp=sharing)
+
+## Supported Models
+Python bindings support the following ggml architectures: `gptj`, `llama`, `mpt`. See API reference for more details.
+
+## Best Practices
+
+There are two methods to interface with the underlying language model, `chat_completion()` and `generate()`. Chat completion formats a user-provided message dictionary into a prompt template (see API documentation for more details and options). This will usually produce much better results and is the approach we recommend. You may also prompt the model with `generate()` which will just pass the raw input string to the model. 
+
+## API Reference
 
 ::: gpt4all.gpt4all.GPT4All
-