I am running inference using the pipeline api. But I get the following warning which recommends using the Dataset api. How can I do so?
transformers4/lib/python3.8/site-packages/transformers/pipelines/base.py:899:
UserWarning: You seem to be using the pipelines sequentially on GPU.
In order to maximize efficiency please use a dataset
warnings.warn()
I found the following help in the documentation, but I haven’t implemented yet because I’m just doing a POC with 50 documents. Sharing now in case it helps you get started!
Having same issue while using T5-base-grammar-correction for grammer correction on my dataframe with text column
rom happytransformer import HappyTextToText
from happytransformer import TTSettings
from tqdm.notebook import tqdm
tqdm.pandas()
happy_tt = HappyTextToText("T5", "./t5-base-grammar-correction")
beam_settings = TTSettings(num_beams=5, min_length=1, max_length=30)
def grammer_pipeline(text):
text = "gec: " + text
result = happy_tt.generate_text(text, args=beam_settings)
return result.text
df['new_text'] = df['original_text'].progress_apply(grammer_pipeline)
It runs very slow and provides the User Warning
/home/.local/lib/python3.6/site-packages/transformers/pipelines/base.py:908: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset
UserWarning,
How to implement this to efficiently utilise GPUs?