Update README.md

README.md

@@ -19,23 +19,9 @@ I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
 
 Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
 
-## Intended uses & limitations
-
-#### How to use
-
-You can use this model directly with a pipeline for text generation:
-
-```python
-from transformers import pipeline
-generator = pipeline('text-generation', model='huggingtweets/l2k')
-generator("My dream is", max_length=50, num_return_sequences=5)
-```
-
-#### Limitations and bias
-
-The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
-
-In addition, the data present in the user's tweets further affects the text generated by the model.
+<a href="https://huggingface.co/exbert/?model=huggingtweets/l2k&modelKind=autoregressive&sentence=I%20love%20huggingtweets!&layer=11">
+	<img width="300px" src="https://hf-dinosaur.huggingface.co/exbert/button.png">
+</a>
 
 ## How does it work?
 
@@ -56,13 +42,31 @@ The model was trained on [@l2k's tweets](https://twitter.com/l2k).
 | Short tweets      | 61 |
 | Tweets kept       | 1886  |
 
-[Explore the data](https://app.wandb.ai/borisd13/huggingtweets/runs/3ahi71lv/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
+[Explore the data](https://app.wandb.ai/borisd13/huggingtweets/runs/17gu0rb2/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
 
 ## Training procedure
 
 The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @l2k's tweets for 4 epochs.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/borisd13/huggingtweets/runs/vzgo90wy).
+Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/borisd13/huggingtweets/runs/3ef1n70z).
+
+## Intended uses & limitations
+
+#### How to use
+
+You can use this model directly with a pipeline for text generation:
+
+```python
+from transformers import pipeline
+generator = pipeline('text-generation', model='huggingtweets/l2k')
+generator("My dream is", max_length=50, num_return_sequences=5)
+```
+
+#### Limitations and bias
+
+The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
+
+In addition, the data present in the user's tweets further affects the text generated by the model.
 
 ## About
 
@@ -73,7 +77,3 @@ Hyperparameters and metrics are recorded in the [W&B training run](https://app.w
 For more details, visit the project repository.
 
 [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
-
-<a href="https://huggingface.co/exbert/?model=huggingtweets/l2k&modelKind=autoregressive&sentence=I%20love%20huggingtweets!&layer=11">
-	<img width="300px" src="https://hf-dinosaur.huggingface.co/exbert/button.png">
-</a>