Add C Transformers for GGML Models (#5218)

# Add C Transformers for GGML Models
I created Python bindings for the GGML models:
https://github.com/marella/ctransformers

Currently it supports GPT-2, GPT-J, GPT-NeoX, LLaMA, MPT, etc. See
[Supported
Models](https://github.com/marella/ctransformers#supported-models).


It provides a unified interface for all models:

```python
from langchain.llms import CTransformers

llm = CTransformers(model='/path/to/ggml-gpt-2.bin', model_type='gpt2')

print(llm('AI is going to'))
```

It can be used with models hosted on the Hugging Face Hub:

```py
llm = CTransformers(model='marella/gpt-2-ggml')
```

It supports streaming:

```py
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler

llm = CTransformers(model='marella/gpt-2-ggml', callbacks=[StreamingStdOutCallbackHandler()])
```

Please see [README](https://github.com/marella/ctransformers#readme) for
more details.
---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>

docs/modules/models/llms/integrations/ctransformers.ipynb

@@ -0,0 +1,125 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# C Transformers\n",
+    "\n",
+    "The [C Transformers](https://github.com/marella/ctransformers) library provides Python bindings for GGML models.\n",
+    "\n",
+    "This example goes over how to use LangChain to interact with `C Transformers` [models](https://github.com/marella/ctransformers#supported-models)."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Install**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install ctransformers"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Load Model**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.llms import CTransformers\n",
+    "\n",
+    "llm = CTransformers(model='marella/gpt-2-ggml')"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Generate Text**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(llm('AI is going to'))"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Streaming**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
+    "\n",
+    "llm = CTransformers(model='marella/gpt-2-ggml', callbacks=[StreamingStdOutCallbackHandler()])\n",
+    "\n",
+    "response = llm('AI is going to')"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**LLMChain**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain import PromptTemplate, LLMChain\n",
+    "\n",
+    "template = \"\"\"Question: {question}\n",
+    "\n",
+    "Answer:\"\"\"\n",
+    "\n",
+    "prompt = PromptTemplate(template=template, input_variables=['question'])\n",
+    "\n",
+    "llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
+    "\n",
+    "response = llm_chain.run('What is AI?')"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}