Text Classification
Transformers
PyTorch
Arabic
English
distilbert
chemistry
biology
finance
legal
music
code
art
climate
medical
emotion
endpoints-template
Inference Endpoints
Zalmati / batch_throttle.py
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from hfapi import Client
client = Client()
BATCH_SIZE = 4
LONG_LIST_OF_INPUTS = [
"I like you. </s></s> I love you.",
"At the other end of Pennsylvania Avenue, people began to line up for a White House tour. </s></s> People formed a line at the end of Pennsylvania Avenue.",
] * 500
def chunker(seq, size):
return (seq[pos:pos + size] for pos in range(0, len(seq), size))
all_results = []
for inputs in chunker(LONG_LIST_OF_INPUTS, BATCH_SIZE):
result = client.text_classification(inputs, model="roberta-large-mnli")
print(result)
all_results += result
print("Done!")