{
  "id": 214449,
  "title": "EfficientNet-PyTorch and pytorchcv.model_provider dataset (install locally).",
  "url": "/competitions/cassava-leaf-disease-classification/discussion/214449",
  "author_name": "",
  "post_date": "2021-01-26T17:44:42.021689100Z",
  "votes": 3,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Many notebooks use timm to create the model. However, for those who use <code>EfficientNet.from_pretrained(\"model\")</code> or <code>ptcv_get_model(\"model\", pretrained=False)</code>, I haven't found the dataset on Kaggle that allows us to install <code>efficientnet_pytorch</code> and <code>pytorchcv</code> locally. </p>\n<p>So I uploaded the latest version of <a href=\"https://www.kaggle.com/leonshangguan/efficientnetpytorch\" target=\"_blank\">EfficientNet-PyTorch</a> and <a href=\"https://www.kaggle.com/leonshangguan/imgclsmob\" target=\"_blank\">\nimgclsmob (pytorcv)</a>. <br>\nFor using, refer to <a href=\"https://www.kaggle.com/leonshangguan/inference-test\" target=\"_blank\">Inference_test</a>.</p>\n<p>Hope it helps.</p>",
  "messages": [
    {
      "id": "1171231",
      "postDate": "01/26/2021 17:44:42",
      "content": "<p>Many notebooks use timm to create the model. However, for those who use <code>EfficientNet.from_pretrained(\"model\")</code> or <code>ptcv_get_model(\"model\", pretrained=False)</code>, I haven't found the dataset on Kaggle that allows us to install <code>efficientnet_pytorch</code> and <code>pytorchcv</code> locally. </p>\n<p>So I uploaded the latest version of <a href=\"https://www.kaggle.com/leonshangguan/efficientnetpytorch\" target=\"_blank\">EfficientNet-PyTorch</a> and <a href=\"https://www.kaggle.com/leonshangguan/imgclsmob\" target=\"_blank\">\nimgclsmob (pytorcv)</a>. <br>\nFor using, refer to <a href=\"https://www.kaggle.com/leonshangguan/inference-test\" target=\"_blank\">Inference_test</a>.</p>\n<p>Hope it helps.</p>",
      "rawMarkdown": "Many notebooks use timm to create the model. However, for those who use `EfficientNet.from_pretrained(\"model\")` or `ptcv_get_model(\"model\", pretrained=False)`, I haven't found the dataset on Kaggle that allows us to install `efficientnet_pytorch` and `pytorchcv` locally. \n\nSo I uploaded the latest version of [EfficientNet-PyTorch](https://www.kaggle.com/leonshangguan/efficientnetpytorch) and [\nimgclsmob (pytorcv)](https://www.kaggle.com/leonshangguan/imgclsmob). \nFor using, refer to [Inference_test](https://www.kaggle.com/leonshangguan/inference-test).\n\nHope it helps.",
      "votes": null
    },
    {
      "id": "1173273",
      "postDate": "01/27/2021 19:02:53",
      "content": "<p>Thank you so much!</p>",
      "rawMarkdown": "Thank you so much!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1173273,
      "author_name": "darknesszx",
      "author_url": "",
      "post_date": "01/27/2021 19:02:53",
      "content": "<p>Thank you so much!</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1171231": "Many notebooks use timm to create the model. However, for those who use `EfficientNet.from_pretrained(\"model\")` or `ptcv_get_model(\"model\", pretrained=False)`, I haven't found the dataset on Kaggle that allows us to install `efficientnet_pytorch` and `pytorchcv` locally. \n\nSo I uploaded the latest version of [EfficientNet-PyTorch](https://www.kaggle.com/leonshangguan/efficientnetpytorch) and [\nimgclsmob (pytorcv)](https://www.kaggle.com/leonshangguan/imgclsmob). \nFor using, refer to [Inference_test](https://www.kaggle.com/leonshangguan/inference-test).\n\nHope it helps.",
    "1173273": "Thank you so much!"
  },
  "source": "meta"
}