Update `gpt4all.mdx` doc (#15392)

The [pyllamacpp](https://github.com/nomic-ai/pyllamacpp) repository has
been archived and the model name and usage need to be changed.

docs/docs/integrations/providers/gpt4all.mdx

@@ -4,8 +4,15 @@ This page covers how to use the `GPT4All` wrapper within LangChain. The tutorial
 
 ## Installation and Setup
 
-- Install the Python package with `pip install pyllamacpp`
-- Download a [GPT4All model](https://github.com/nomic-ai/pyllamacpp#supported-model) and place it in your desired directory
+- Install the Python package with `pip install gpt4all`
+- Download a [GPT4All model](https://gpt4all.io/index.html) and place it in your desired directory
+
+In this example, We are using `mistral-7b-openorca.Q4_0.gguf`(Best overall fast chat model):
+
+```bash
+mkdir models
+wget https://gpt4all.io/models/gguf/mistral-7b-openorca.Q4_0.gguf -O models/mistral-7b-openorca.Q4_0.gguf
+```
 
 ## Usage
 
@@ -17,7 +24,7 @@ To use the GPT4All wrapper, you need to provide the path to the pre-trained mode
 from langchain.llms import GPT4All
 
 # Instantiate the model. Callbacks support token-wise streaming
-model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8)
+model = GPT4All(model="./models/mistral-7b-openorca.Q4_0.gguf", n_threads=8)
 
 # Generate text
 response = model("Once upon a time, ")
@@ -35,7 +42,7 @@ from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
 # from langchain.callbacks.streamlit import StreamlitCallbackHandler
 
 callbacks = [StreamingStdOutCallbackHandler()]
-model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8)
+model = GPT4All(model="./models/mistral-7b-openorca.Q4_0.gguf", n_threads=8)
 
 # Generate text. Tokens are streamed through the callback manager.
 model("Once upon a time, ", callbacks=callbacks)
@@ -43,6 +50,6 @@ model("Once upon a time, ", callbacks=callbacks)
 
 ## Model File
 
-You can find links to model file downloads in the [pyllamacpp](https://github.com/nomic-ai/pyllamacpp) repository.
+You can find links to model file downloads in the [https://gpt4all.io/](https://gpt4all.io/index.html).
 
 For a more detailed walkthrough of this, see [this notebook](/docs/integrations/llms/gpt4all)