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Update README.md

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@@ -51,7 +51,7 @@ The model was trained on [@elonmusk's tweets](https://twitter.com/elonmusk).
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  <tbody style='border-width:0'>
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  <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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  <td style='border-width:0'>Tweets downloaded</td>
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- <td style='border-width:0'>3205</td>
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  </tr>
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  <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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  <td style='border-width:0'>Retweets</td>
@@ -59,24 +59,24 @@ The model was trained on [@elonmusk's tweets](https://twitter.com/elonmusk).
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  </tr>
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  <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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  <td style='border-width:0'>Short tweets</td>
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- <td style='border-width:0'>788</td>
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  </tr>
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  <tr style='border-width:0'>
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  <td style='border-width:0'>Tweets kept</td>
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- <td style='border-width:0'>2185</td>
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  </tr>
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  </tbody>
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  </table>
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- [Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/zgs17gtv/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
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  ## Training procedure
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  The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @elonmusk's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/31b2t7r3) for full transparency and reproducibility.
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- At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/31b2t7r3/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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@@ -102,7 +102,7 @@ In addition, the data present in the user's tweets further affects the text gene
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  </section>
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- [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/borisdayma)
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  <section class='prose'>
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  For more details, visit the project repository.
 
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  <tbody style='border-width:0'>
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  <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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  <td style='border-width:0'>Tweets downloaded</td>
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+ <td style='border-width:0'>3218</td>
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  </tr>
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  <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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  <td style='border-width:0'>Retweets</td>
 
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  </tr>
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  <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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  <td style='border-width:0'>Short tweets</td>
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+ <td style='border-width:0'>791</td>
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  </tr>
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  <tr style='border-width:0'>
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  <td style='border-width:0'>Tweets kept</td>
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+ <td style='border-width:0'>2195</td>
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  </tr>
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  </tbody>
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  </table>
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+ [Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/25auv43h/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
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  ## Training procedure
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  The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @elonmusk's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/8fhm8rjo) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/8fhm8rjo/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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  </section>
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+ [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)
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  <section class='prose'>
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  For more details, visit the project repository.