wehub-resource-sync
91 lines
3.7 KiB
Python
91 lines
3.7 KiB
Python
from transformers import AutoModelForSeq2SeqLM
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from omnihub.frameworks.huggingface import HuggingFaceModelHub
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from omnihub.frameworks.keras import KerasModelHub
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from omnihub.frameworks.onnx import OnnxModelHub
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from omnihub.frameworks.pytorch import PytorchModelHub
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from omnihub.frameworks.tensorflow import TensorflowModelHub
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keras_model_hub = KerasModelHub()
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keras_urls = [
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#'vgg19/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5',
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# 'vgg19/vgg19_weights_tf_dim_ordering_tf_kernels.h5',
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# bug in downloader? Seems to be stalled at the last few bytes, skipping for now
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#'vgg16/vgg16_weights_tf_dim_ordering_tf_kernels.h5',
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#'vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5',
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'resnet50/notop',
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'resnet50/top',
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'resnet101/notop',
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'resnet101/top',
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'resnet152/notop',
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'resnet152/top',
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'resnet50v2/notop',
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'resnet50v2/top',
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'resnet101v2/notop',
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'resnet101v2/top',
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'resnet152v2/notop',
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'resnet152v2/top',
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'densenet121/notop',
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'densenet121/top',
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'densenet169/notop',
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'densenet169/top',
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'densenet201/notop',
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'densenet201/top',
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'inceptionresnetv2/notop',
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'inceptionresnetv2/top',
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'mobilenet/notop',
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'mobilenet/top',
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'mobilenetv2/notop',
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'mobilenetv2/top',
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#'mobilenetv3/notop',
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#'mobilenetv3/top',
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'nasnet/notop',
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'nasnet/top',
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'nasnet_mobile/notop',
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'nasnet_mobile/top',
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'xception/notop',
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'xception/top',
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]
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for i in range(0,8):
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keras_urls.append(f'efficientnetb{i}')
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#for url in keras_urls:
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# keras_model_hub.download_model(url)
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onnx_model_hub = OnnxModelHub()
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onnx_urls = ['vision/body_analysis/age_gender/models/age_googlenet.onnx',
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'vision/body_analysis/age_gender/models/gender_googlenet.onnx',
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'vision/body_analysis/age_gender/models/vgg_ilsvrc_16_age_chalearn_iccv2015.onnx',
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'vision/body_analysis/age_gender/models/vgg_ilsvrc_16_age_imdb_wiki.onnx',
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'vision/body_analysis/age_gender/models/vgg_ilsvrc_16_gender_imdb_wiki.onnx',
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'vision/body_analysis/arcface/model/arcfaceresnet100-8.onnx',
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'vision/body_analysis/emotion_ferplus/model/emotion-ferplus-2.onnx',
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'vision/body_analysis/emotion_ferplus/model/emotion-ferplus-7.onnx',
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'vision/body_analysis/emotion_ferplus/model/emotion-ferplus-8.onnx',
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'vision/body_analysis/ultraface/models/version-RFB-320.onnx',
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'vision/body_analysis/ultraface/models/version-RFB-640.onnx',
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'vision/classification/alexnet/model/bvlcalexnet-12-int8.onnx',
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'vision/classification/alexnet/model/bvlcalexnet-12.onnx',
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'vision/classification/caffenet/model/caffenet-12-int8.onnx',
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'vision/classification/caffenet/model/caffenet-12.onnx',
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'vision/classification/efficientnet-lite4/model/efficientnet-lite4-11.onnx'
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]
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#for url in onnx_urls:
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# onnx_model_hub.download_model(url)
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tensorflow_model_hub = TensorflowModelHub()
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tensorflow_urls = ['emilutz/vgg19-block4-conv2-unpooling-decoder/1']
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for url in tensorflow_urls:
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tensorflow_model_hub.download_model(url)
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pytorch_model_hub = PytorchModelHub()
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pytorch_urls = ['resnet18']
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for url in pytorch_urls:
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pytorch_model_hub.download_model(url)
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huggingface_model_hub = HuggingFaceModelHub()
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frameworks = ['tensorflow','pytorch']
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huggingface_urls = [ 'gpt2','bert-base-uncased','t5-base','bert-base-chinese','google/electra-small-discriminator','facebook/wav2vec2-base-960h','facebook/bart-large-cnn']
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huggingface_urls = ['facebook/bart-large-cnn']
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for url in huggingface_urls:
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for framework_name in frameworks:
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huggingface_model_hub.download_model(url,framework_name=framework_name)
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