mirror of
https://github.com/hwchase17/langchain
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350 lines
8.3 KiB
Plaintext
350 lines
8.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "959300d4",
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"metadata": {},
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"source": [
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"# Hugging Face Hub\n",
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"\n",
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">The [Hugging Face Hub](https://huggingface.co/docs/hub/index) is a platform with over 120k models, 20k datasets, and 50k demo apps (Spaces), all open source and publicly available, in an online platform where people can easily collaborate and build ML together.\n",
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"\n",
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"This example showcases how to connect to the `Hugging Face Hub` and use different models."
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]
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},
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{
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"cell_type": "markdown",
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"id": "1ddafc6d-7d7c-48fa-838f-0e7f50895ce3",
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"metadata": {},
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"source": [
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"## Installation and Setup"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4c1b8450-5eaf-4d34-8341-2d785448a1ff",
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"metadata": {
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"tags": []
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},
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"source": [
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"To use, you should have the ``huggingface_hub`` python [package installed](https://huggingface.co/docs/huggingface_hub/installation)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "d772b637-de00-4663-bd77-9bc96d798db2",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"!pip install huggingface_hub"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "d597a792-354c-4ca5-b483-5965eec5d63d",
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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" ········\n"
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]
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}
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],
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"source": [
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"# get a token: https://huggingface.co/docs/api-inference/quicktour#get-your-api-token\n",
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"\n",
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"from getpass import getpass\n",
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"\n",
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"HUGGINGFACEHUB_API_TOKEN = getpass()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "b8c5b88c-e4b8-4d0d-9a35-6e8f106452c2",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"os.environ[\"HUGGINGFACEHUB_API_TOKEN\"] = HUGGINGFACEHUB_API_TOKEN"
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]
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},
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{
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"cell_type": "markdown",
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"id": "84dd44c1-c428-41f3-a911-520281386c94",
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"metadata": {},
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"source": [
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"## Prepare Examples"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3fe7d1d1-241d-426a-acff-e208f1088871",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain import HuggingFaceHub"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "6620f39b-3d32-4840-8931-ff7d2c3e47e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain import PromptTemplate, LLMChain"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "44adc1a0-9c0a-4f1e-af5a-fe04222e78d7",
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"metadata": {},
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"outputs": [],
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"source": [
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"question = \"Who won the FIFA World Cup in the year 1994? \"\n",
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"\n",
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"template = \"\"\"Question: {question}\n",
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"\n",
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"Answer: Let's think step by step.\"\"\"\n",
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"\n",
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"prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ddaa06cf-95ec-48ce-b0ab-d892a7909693",
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"metadata": {},
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"source": [
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"## Examples\n",
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"\n",
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"Below are some examples of models you can access through the `Hugging Face Hub` integration."
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]
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},
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{
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"cell_type": "markdown",
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"id": "4c16fded-70d1-42af-8bfa-6ddda9f0bc63",
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"metadata": {},
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"source": [
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"### Flan, by Google"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "39c7eeac-01c4-486b-9480-e828a9e73e78",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"repo_id = \"google/flan-t5-xxl\" # See https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads for some other options"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "3acf0069",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The FIFA World Cup was held in the year 1994. West Germany won the FIFA World Cup in 1994\n"
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]
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}
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],
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"source": [
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"llm = HuggingFaceHub(\n",
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" repo_id=repo_id, model_kwargs={\"temperature\": 0.5, \"max_length\": 64}\n",
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")\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"\n",
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"print(llm_chain.run(question))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1a5c97af-89bc-4e59-95c1-223742a9160b",
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"metadata": {},
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"source": [
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"### Dolly, by Databricks\n",
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"\n",
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"See [Databricks](https://huggingface.co/databricks) organization page for a list of available models."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "521fcd2b-8e38-4920-b407-5c7d330411c9",
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"metadata": {},
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"outputs": [],
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"source": [
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"repo_id = \"databricks/dolly-v2-3b\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "9907ec3a-fe0c-4543-81c4-d42f9453f16c",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" First of all, the world cup was won by the Germany. Then the Argentina won the world cup in 2022. So, the Argentina won the world cup in 1994.\n",
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"\n",
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"\n",
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"Question: Who\n"
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]
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}
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],
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"source": [
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"llm = HuggingFaceHub(\n",
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" repo_id=repo_id, model_kwargs={\"temperature\": 0.5, \"max_length\": 64}\n",
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")\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"print(llm_chain.run(question))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "03f6ae52-b5f9-4de6-832c-551cb3fa11ae",
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"metadata": {},
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"source": [
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"### Camel, by Writer\n",
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"\n",
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"See [Writer's](https://huggingface.co/Writer) organization page for a list of available models."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "257a091d-750b-4910-ac08-fe1c7b3fd98b",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"repo_id = \"Writer/camel-5b-hf\" # See https://huggingface.co/Writer for other options"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b06f6838-a11a-4d6a-88e3-91fa1747a2b3",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = HuggingFaceHub(\n",
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" repo_id=repo_id, model_kwargs={\"temperature\": 0.5, \"max_length\": 64}\n",
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")\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"print(llm_chain.run(question))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2bf838eb-1083-402f-b099-b07c452418c8",
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"metadata": {},
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"source": [
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"### XGen, by Salesforce\n",
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"\n",
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"See [more information](https://github.com/salesforce/xgen)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "18c78880-65d7-41d0-9722-18090efb60e9",
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"metadata": {},
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"outputs": [],
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"source": [
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"repo_id = \"Salesforce/xgen-7b-8k-base\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1b1150b4-ec30-4674-849e-6a41b085aa2b",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = HuggingFaceHub(\n",
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" repo_id=repo_id, model_kwargs={\"temperature\": 0.5, \"max_length\": 64}\n",
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")\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"print(llm_chain.run(question))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0aca9f9e-f333-449c-97b2-10d1dbf17e75",
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"metadata": {},
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"source": [
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"### Falcon, by Technology Innovation Institute (TII)\n",
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"\n",
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"See [more information](https://huggingface.co/tiiuae/falcon-40b)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "496b35ac-5ee2-4b68-a6ce-232608f56c03",
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"metadata": {},
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"outputs": [],
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"source": [
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"repo_id = \"tiiuae/falcon-40b\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ff2541ad-e394-4179-93c2-7ae9c4ca2a25",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = HuggingFaceHub(\n",
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" repo_id=repo_id, model_kwargs={\"temperature\": 0.5, \"max_length\": 64}\n",
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")\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"print(llm_chain.run(question))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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