langchain/docs/extras/integrations/llms/huggingface_textgen_inference.ipynb
2023-07-23 23:23:16 -07:00

110 lines
2.7 KiB
Plaintext

{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Huggingface TextGen Inference\n",
"\n",
"[Text Generation Inference](https://github.com/huggingface/text-generation-inference) is a Rust, Python and gRPC server for text generation inference. Used in production at [HuggingFace](https://huggingface.co/) to power LLMs api-inference widgets.\n",
"\n",
"This notebooks goes over how to use a self hosted LLM using `Text Generation Inference`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To use, you should have the `text_generation` python package installed."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# !pip3 install text_generation"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain.llms import HuggingFaceTextGenInference\n",
"\n",
"llm = HuggingFaceTextGenInference(\n",
" inference_server_url=\"http://localhost:8010/\",\n",
" max_new_tokens=512,\n",
" top_k=10,\n",
" top_p=0.95,\n",
" typical_p=0.95,\n",
" temperature=0.01,\n",
" repetition_penalty=1.03,\n",
")\n",
"llm(\"What did foo say about bar?\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Streaming"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain.llms import HuggingFaceTextGenInference\n",
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
"\n",
"\n",
"llm = HuggingFaceTextGenInference(\n",
" inference_server_url=\"http://localhost:8010/\",\n",
" max_new_tokens=512,\n",
" top_k=10,\n",
" top_p=0.95,\n",
" typical_p=0.95,\n",
" temperature=0.01,\n",
" repetition_penalty=1.03,\n",
" stream=True\n",
")\n",
"llm(\"What did foo say about bar?\", callbacks=[StreamingStdOutCallbackHandler()])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
},
"vscode": {
"interpreter": {
"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}