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Runtime error
| import gradio as gr | |
| from langchain.llms import HuggingFaceHub | |
| from langchain.prompts import PromptTemplate | |
| from langchain.chains import LLMChain | |
| def predict(question): | |
| from langchain.llms import HuggingFaceHub | |
| from langchain.prompts import PromptTemplate | |
| from langchain.chains import LLMChain | |
| template = """Question: {question} | |
| Answer: Let's think step by step.""" | |
| prompt = PromptTemplate(template=template, input_variables=["question"]) | |
| #repo_id = "google/flan-t5-xxl" # See https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads for some other options | |
| #repo_id = "HuggingFaceH4/starchat-beta" | |
| repo_id = "meta-llama/Llama-2-70b-chat-hf" | |
| # repo_id = "tiiuae/falcon-180B-chat" | |
| #llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 1024}) | |
| #llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"min_length":100, "max_new_tokens":1024, "do_sample":True, "temperature":0.1,"top_k":50, "top_p":0.95, "eos_token_id":49155}) | |
| llm = HuggingFaceHub(repo_id=repo_id) | |
| llm_chain = LLMChain(prompt=prompt, llm=llm) | |
| initial_response=llm_chain.run(question) | |
| temp_ai_response=str(initial_response) | |
| #final_ai_response=temp_ai_response.partition('<|end|>')[0] | |
| #return final_ai_response | |
| return temp_ai_response | |
| gr.Interface(fn=predict, inputs="text", outputs="text").launch() | |