!pip install sentencepiece --upgrade
!pip install transformers --upgrade
from transformers import pipeline,AutoModel,AutoTokenizer
model =AutoModel.from_pretrained("microsoft/deberta-v2-xxlarge-mnli")
tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-v2-xxlarge")
classifier = pipeline("zero-shot-classification",model=model,tokenizer=tokenizer)
sequence = "Bob: Hey, how is work going? , Amy: Good, I wanted to talk to you about your work performance."
candidate_labels = ["Bob is talking about the same topic as Amy.", "Amy explained to Bob why he is not doing well.", "Bob asked how Amy is.", "Bob brought up the topic of work performance."]
print(classifier(sequence, candidate_labels))
also, how do I fine-tune such a model for my purpose?
Were you able to solve the issue? I’m having the same issue.
Hi,
You need to replace AutoModel
by AutoModelForSequenceClassification
in the code snippet above (since AutoModel
doesn’t include a classification head on top).