Upload README.md

README.md

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+
+Site Reliability Engineering
 ---
 language: en
 thumbnail: http://www.huggingtweets.com/slime_machine/1640253262516/predictions.png
 tags:
 - huggingtweets
-- customtag-test
 widget:
 - text: "My dream is"
 ---
+
 <div class="inline-flex flex-col" style="line-height: 1.5;">
     <div class="flex">
         <div
@@ -22,4 +24,64 @@ widget:
     <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
     <div style="text-align: center; font-size: 16px; font-weight: 800">rich homie cron</div>
     <div style="text-align: center; font-size: 14px;">@slime_machine</div>
-</div>
+</div>
+
+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)!
+
+## How does it work?
+
+The model uses the following pipeline.
+
+![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
+
+To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
+
+## Training data
+
+The model was trained on tweets from rich homie cron.
+
+| Data | rich homie cron |
+| --- | --- |
+| Tweets downloaded | 3234 |
+| Retweets | 590 |
+| Short tweets | 494 |
+| Tweets kept | 2150 |
+
+[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/28uf2bgx/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 @slime_machine's tweets.
+
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3h5ua6ik) for full transparency and reproducibility.
+
+At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3h5ua6ik/artifacts) is logged and versioned.
+
+## 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/slime_machine')
+generator("My dream is", 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
+
+*Built by Boris Dayma*
+
+[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)
+
+For more details, visit the project repository.
+
+[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)