URIAL¶
Generates a response using a non-instruct fine-tuned model.
URIAL is a pre-defined task that generates a response using a non-instruct fine-tuned
model. This task is used to generate a response based on the conversation provided as
input.
Input & Output Columns¶
Inputs¶
-
instruction (
str, optional): The instruction to generate a response from. -
conversation (
List[Dict[str, str]], optional): The conversation to generate a response from (the last message must be from the user).
Outputs¶
-
generation (
str): The generated response. -
model_name (
str): The name of the model used to generate the response.
Examples¶
Generate text from an instruction¶
from distilabel.models import vLLM
from distilabel.steps.tasks import URIAL
step = URIAL(
llm=vLLM(
model="meta-llama/Meta-Llama-3.1-8B",
generation_kwargs={"temperature": 0.7},
),
)
step.load()
results = next(
step.process(inputs=[{"instruction": "What's the most most common type of cloud?"}])
)
# [
# {
# 'instruction': "What's the most most common type of cloud?",
# 'generation': 'Clouds are classified into three main types, high, middle, and low. The most common type of cloud is the middle cloud.',
# 'distilabel_metadata': {...},
# 'model_name': 'meta-llama/Meta-Llama-3.1-8B'
# }
# ]