Albert pretrained weights change across runs. 
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): TFAlbertModel 

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts: (give details below)
```
import tensorflow as tf
from transformers import AlbertTokenizer, TFAlbertModel

tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')
model = TFAlbertModel.from_pretrained('albert-base-v2')
model.summary()

print(len(model.trainable_weights))

print(model.trainable_weights[23])

input_ids = tf.constant(tokenizer.encode("Hello, my dog is cute"))[None, :]

outputs = model(input_ids)

print(outputs[0].shape, outputs[1].shape, len(outputs))
last_hidden_states = outputs[0]

print(last_hidden_states)
```
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [X] my own task or dataset: (give details below)
Trying to load pre-trained weights
## To reproduce
Run the code above two times and you will see that the weights of the model are not the same across the two runs
Steps to reproduce the behavior:

1. Run the code the first time and log the output
2. Run the code a second time and log the output
3. Check that the two logs are not the same.

## Expected behavior

Since the model is loading pre-trained weights the results should be the same across runs.

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 2.11.0
- Platform: Linux-4.4.0-179-generic-x86_64-with-debian-stretch-sid
- Python version: 3.6.9
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): 2.0.1 (True)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

I apologize if the issue is due to me misusing your library, first time using Albert.
I just did the same experiment with Roberta weights and did not have the same issue.<|||||>Hi, I can reproduce. This is due to the archive maps not being available anymore, and therefore the wrong ALBERT models are linked.

Thanks for raising the issue, this is quite a bug.

cc @julien-c <|||||>My bad! It's my fault. I added a warning to the release notes about this: https://github.com/huggingface/transformers/releases/tag/v2.11.0<|||||>Is there a plan to fix this? Looks like the issue is that the "real" model we want is named `with-prefix-tf_model.h5`, which needs to be renamed to `tf_model.h5`. https://huggingface.co/albert-base-v2#list-files<|||||>This should work now, the weights have been changed to use the `with-prefix` weights.<|||||>Thanks !! 