Updated README

Author: lukemelas

README.md

@@ -1,9 +1,17 @@
 # EfficientNet PyTorch
 
-### Update (June 29, 2019)
+### Update (July 31, 2019)
 
 _Upgrade the pip package with_ `pip install --upgrade efficientnet-pytorch`
 
+The B6 and B7 models are now available. Additionally, _all_ pretrained models have been updated to use AutoAugment preprocessing, which translates to better performance across the board. Usage is the same as before: 
+```python
+from efficientnet_pytorch import EfficientNet
+model = EfficientNet.from_pretrained('efficientnet-b7') 
+```
+
+### Update (June 29, 2019)
+
 This update adds easy model exporting ([#20](https://github.com/lukemelas/EfficientNet-PyTorch/issues/20)) and feature extraction ([#38](https://github.com/lukemelas/EfficientNet-PyTorch/issues/38)). 
 
  * [Example: Export to ONNX](#example-export)

tf_to_pytorch/README.md

@@ -7,7 +7,7 @@ I should also emphasize that you do *not* need to run any of this code to load p
 That being said, the main script here is `convert_to_tf/load_tf_weights.py`. In order to use it, you should first download the pretrained TensorFlow weights:
  ```bash
 cd pretrained_tensorflow
-./download.sh
+./download.sh efficientnet-b0
 cd ..
 ```
 Then

tf_to_pytorch/pretrained_tensorflow/download.sh

@@ -9,6 +9,6 @@
 #   ./download.sh efficientnet-b3
 
 MODEL=$1
-wget https://storage.googleapis.com/cloud-tpu-checkpoints/efficientnet/${MODEL}.tar.gz
+wget https://storage.googleapis.com/cloud-tpu-checkpoints/efficientnet/ckptsaug/${MODEL}.tar.gz
 tar xvf ${MODEL}.tar.gz
 rm ${MODEL}.tar.gz