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improves huggingface_hub example (#988)

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The provided example uses the default `max_length` of `20` tokens, which
leads to the example generation getting cut off. 20 tokens is way too
short to show CoT reasoning, so I boosted it to `64`.

Without knowing HF's API well, it can be hard to figure out just where
those `model_kwargs` come from, and `max_length` is a super critical
one.
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Charles Frye 2023-02-10 17:56:15 -08:00 committed by GitHub
parent c2d1d903fa
commit e9799d6821
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1 changed files with 2 additions and 2 deletions
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docs/modules/llms/integrations/huggingface_hub.ipynb
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@ -20,7 +20,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"The Seattle Seahawks won the Super Bowl in 2010. Justin Beiber was born in 2010. The\n"
"The Seattle Seahawks won the Super Bowl in 2010. Justin Beiber was born in 2010. The final answer: Seattle Seahawks.\n"
]
}
],
@ -31,7 +31,7 @@
"\n",
"Answer: Let's think step by step.\"\"\"\n",
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])\n",
"llm_chain = LLMChain(prompt=prompt, llm=HuggingFaceHub(repo_id=\"google/flan-t5-xl\", model_kwargs={\"temperature\":1e-10}))\n",
"llm_chain = LLMChain(prompt=prompt, llm=HuggingFaceHub(repo_id=\"google/flan-t5-xl\", model_kwargs={\"temperature\":0, \"max_length\":64}))\n",
"\n",
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
"\n",