Prompts for Question Answering Assistant
#21
by
pratikhublikar
- opened
I am building a question answering assistant using the model. What prompts can I use so that the responses generated by the model are brief, to the point and coherent?
An example using Langchain's prompts
:
from langchain.llms import CTransformers
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
model_path : str = "models/Llama-2-7B-Chat-GGML/llama-2-7b-chat.ggmlv3.q4_0.bin"
llm = CTransformers(
model=model_path,
model_type='llama',
)
prompt = PromptTemplate(
input_variables=["product"],
template="What is a good name for a company that makes {product}? Answer with a simple list only.",
)
llmchain = LLMChain(llm=llm, prompt=prompt)
print(llmchain.run("podcast player"))
The prompt template of Llama2 is <s>[INST]\n<<SYS>>\n{system_prompt}\n<</SYS>>\n\n{user_prompt}[/INST]
(ref. https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat/blob/main/model.py). Does CTransformers library handles this automatically? Otherwise how can it work your example? Thanks, Vincenzo
The PR that dealing with this issue just got merged: https://github.com/huggingface/transformers/pull/25323