Pipeline testing - using tiny models on Hub (#20426)
* rework pipeline tests * run pipeline tests * fix * fix * fix * revert the changes in get_test_pipeline() parameter list * fix expected error message * skip a test * clean up --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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@@ -36,7 +36,7 @@ else:
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class VisualQuestionAnsweringPipelineTests(unittest.TestCase, metaclass=PipelineTestCaseMeta):
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model_mapping = MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING
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def get_test_pipeline(self, model, tokenizer, feature_extractor, image_processor):
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def get_test_pipeline(self, model, tokenizer, processor):
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vqa_pipeline = pipeline("visual-question-answering", model="hf-internal-testing/tiny-vilt-random-vqa")
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examples = [
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{
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