diff --git a/docs/extras/modules/model_io/models/llms/integrations/gpt4all.ipynb b/docs/extras/modules/model_io/models/llms/integrations/gpt4all.ipynb
index 35dc908e0e..7ebbd4e9e2 100644
--- a/docs/extras/modules/model_io/models/llms/integrations/gpt4all.ipynb
+++ b/docs/extras/modules/model_io/models/llms/integrations/gpt4all.ipynb
@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
     "tags": []
    },
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {
     "tags": []
    },
@@ -64,13 +64,20 @@
    "source": [
     "### Specify Model\n",
     "\n",
-    "To run locally, download a compatible ggml-formatted model. For more info, visit https://github.com/nomic-ai/gpt4all\n",
+    "To run locally, download a compatible ggml-formatted model. \n",
+    " \n",
+    "**Download option 1**: The [gpt4all page](https://gpt4all.io/index.html) has a useful `Model Explorer` section:\n",
     "\n",
-    "For full installation instructions go [here](https://gpt4all.io/index.html).\n",
+    "* Select a model of interest\n",
+    "* Download using the UI and move the `.bin` to the `local_path` (noted below)\n",
     "\n",
-    "The GPT4All Chat installer needs to decompress a 3GB LLM model during the installation process!\n",
+    "For more info, visit https://github.com/nomic-ai/gpt4all.\n",
     "\n",
-    "Note that new models are uploaded regularly - check the link above for the most recent `.bin` URL"
+    "--- \n",
+    "\n",
+    "**Download option 2**: Uncomment the below block to download a model. \n",
+    "\n",
+    "* You may want to update `url` to a new version, whih can be browsed using the [gpt4all page](https://gpt4all.io/index.html)."
    ]
   },
   {
@@ -81,22 +88,8 @@
    "source": [
     "local_path = (\n",
     "    \"./models/ggml-gpt4all-l13b-snoozy.bin\"  # replace with your desired local file path\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Uncomment the below block to download a model. You may want to update `url` to a new version."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
+    ")\n",
+    "\n",
     "# import requests\n",
     "\n",
     "# from pathlib import Path\n",
@@ -126,8 +119,10 @@
    "source": [
     "# Callbacks support token-wise streaming\n",
     "callbacks = [StreamingStdOutCallbackHandler()]\n",
+    "\n",
     "# Verbose is required to pass to the callback manager\n",
     "llm = GPT4All(model=local_path, callbacks=callbacks, verbose=True)\n",
+    "\n",
     "# If you want to use a custom model add the backend parameter\n",
     "# Check https://docs.gpt4all.io/gpt4all_python.html for supported backends\n",
     "llm = GPT4All(model=local_path, backend=\"gptj\", callbacks=callbacks, verbose=True)"
@@ -170,7 +165,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.2"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,
diff --git a/langchain/llms/gpt4all.py b/langchain/llms/gpt4all.py
index b9d37ad38c..24a994b55a 100644
--- a/langchain/llms/gpt4all.py
+++ b/langchain/llms/gpt4all.py
@@ -19,7 +19,7 @@ class GPT4All(LLM):
         .. code-block:: python
 
             from langchain.llms import GPT4All
-            model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8)
+            model = GPT4All(model="./models/gpt4all-model.bin", n_threads=8)
 
             # Simplest invocation
             response = model("Once upon a time, ")
@@ -30,7 +30,7 @@ class GPT4All(LLM):
 
     backend: Optional[str] = Field(None, alias="backend")
 
-    n_ctx: int = Field(512, alias="n_ctx")
+    max_tokens: int = Field(200, alias="max_tokens")
     """Token context window."""
 
     n_parts: int = Field(-1, alias="n_parts")
@@ -61,10 +61,10 @@ class GPT4All(LLM):
     n_predict: Optional[int] = 256
     """The maximum number of tokens to generate."""
 
-    temp: Optional[float] = 0.8
+    temp: Optional[float] = 0.7
     """The temperature to use for sampling."""
 
-    top_p: Optional[float] = 0.95
+    top_p: Optional[float] = 0.1
     """The top-p value to use for sampling."""
 
     top_k: Optional[int] = 40
@@ -79,19 +79,15 @@ class GPT4All(LLM):
     repeat_last_n: Optional[int] = 64
     "Last n tokens to penalize"
 
-    repeat_penalty: Optional[float] = 1.3
+    repeat_penalty: Optional[float] = 1.18
     """The penalty to apply to repeated tokens."""
 
-    n_batch: int = Field(1, alias="n_batch")
+    n_batch: int = Field(8, alias="n_batch")
     """Batch size for prompt processing."""
 
     streaming: bool = False
     """Whether to stream the results or not."""
 
-    context_erase: float = 0.5
-    """Leave (n_ctx * context_erase) tokens
-    starting from beginning if the context has run out."""
-
     allow_download: bool = False
     """If model does not exist in ~/.cache/gpt4all/, download it."""
 
@@ -105,7 +101,7 @@ class GPT4All(LLM):
     @staticmethod
     def _model_param_names() -> Set[str]:
         return {
-            "n_ctx",
+            "max_tokens",
             "n_predict",
             "top_k",
             "top_p",
@@ -113,12 +109,11 @@ class GPT4All(LLM):
             "n_batch",
             "repeat_penalty",
             "repeat_last_n",
-            "context_erase",
         }
 
     def _default_params(self) -> Dict[str, Any]:
         return {
-            "n_ctx": self.n_ctx,
+            "max_tokens": self.max_tokens,
             "n_predict": self.n_predict,
             "top_k": self.top_k,
             "top_p": self.top_p,
@@ -126,7 +121,6 @@ class GPT4All(LLM):
             "n_batch": self.n_batch,
             "repeat_penalty": self.repeat_penalty,
             "repeat_last_n": self.repeat_last_n,
-            "context_erase": self.context_erase,
         }
 
     @root_validator()