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License: Apache License 2.0
Accelerated NLP pipelines for fast inference on CPU. Built with Transformers and ONNX runtime.
License: Apache License 2.0
Hi!
What about Bart summarization convertation?
Hello, are you planning to add text generation pipeline? The pipeline implementation is super easy to implement, thanks.
when I run onnx_transformers\notebooks\benchmark_pipelines.ipynb,I got error below:
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Unexpected input data type.
only use nlp_torch = pipeline("feature-extraction", onnx=False),get the inference time figure.
Needs updated imports for transformers 4+
Hi
I am getting an error when running the example
from onnx_transformers import pipeline
# Initialize a pipeline by passing the task name and
# set onnx to True (default value is also True)
nlp = pipeline("sentiment-analysis", onnx=True)
nlp("Transformers and onnx runtime is an awesome combo!")
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-6-b6b36e52d5ec> in <module>
----> 1 from onnx_transformers import pipeline
2
3 # Initialize a pipeline by passing the task name and
4 # set onnx to True (default value is also True)
5 nlp = pipeline("sentiment-analysis", onnx=True)
/opt/anaconda3/lib/python3.8/site-packages/onnx_transformers/__init__.py in <module>
2
3 # Pipelines
----> 4 from .pipelines import (
5 CsvPipelineDataFormat,
6 JsonPipelineDataFormat,
/opt/anaconda3/lib/python3.8/site-packages/onnx_transformers/pipelines.py in <module>
16 from onnxruntime import GraphOptimizationLevel, InferenceSession, SessionOptions, get_all_providers
17 from psutil import cpu_count
---> 18 from transformers.configuration_auto import AutoConfig
19 from transformers.configuration_utils import PretrainedConfig
20 from transformers.convert_graph_to_onnx import convert_pytorch, convert_tensorflow, infer_shapes
ModuleNotFoundError: No module named 'transformers.configuration_auto'
Kindly help
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