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67 lines
3.6 KiB
Plaintext
67 lines
3.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "3acf0069",
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"metadata": {},
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"outputs": [
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{
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"ename": "ValidationError",
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"evalue": "1 validation error for HuggingFaceHub\n__root__\n Did not find HuggingFace API token, please add an environment variable `HUGGINGFACEHUB_API_TOKEN` which contains it. (type=value_error)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValidationError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m/var/folders/y6/8_bzdg295ld6s1_97_12m4lr0000gn/T/ipykernel_56760/1512947828.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m Answer: Let's think step by step.\"\"\"\n\u001b[1;32m 6\u001b[0m \u001b[0mprompt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPrompt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtemplate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtemplate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput_variables\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"question\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mllm_chain\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLLMChain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mllm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mHuggingFaceHub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"gpt2\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtemperature\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1e-10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mquestion\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/workplace/langchain/.venv/lib/python3.7/site-packages/pydantic/main.cpython-37m-darwin.so\u001b[0m in \u001b[0;36mpydantic.main.BaseModel.__init__\u001b[0;34m()\u001b[0m\n",
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"\u001b[0;31mValidationError\u001b[0m: 1 validation error for HuggingFaceHub\n__root__\n Did not find HuggingFace API token, please add an environment variable `HUGGINGFACEHUB_API_TOKEN` which contains it. (type=value_error)"
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]
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}
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],
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"source": [
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"from langchain import Prompt, HuggingFaceHub, LLMChain\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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"prompt = Prompt(template=template, input_variables=[\"question\"])\n",
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"llm_chain = LLMChain(prompt=prompt, llm=HuggingFaceHub(repo_id=\"gpt2\", temperature=1e-10))\n",
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"\n",
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"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
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"\n",
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"llm_chain.predict(question=question)"
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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": "ae4559c7",
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.7.6"
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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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