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Update README.md

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  1. README.md +7 -7
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@@ -51,11 +51,11 @@ The model was trained on [@nvidia's tweets](https://twitter.com/nvidia).
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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'>3243</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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- <td style='border-width:0'>1877</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>
@@ -63,20 +63,20 @@ The model was trained on [@nvidia's tweets](https://twitter.com/nvidia).
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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'>1348</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/8ttno1qs/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 @nvidia's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/2g1wji0l) for full transparency and reproducibility.
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- At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/2g1wji0l/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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@@ -110,4 +110,4 @@ For more details, visit the project repository.
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  [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
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- <!--- random size file -->
 
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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'>3222</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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+ <td style='border-width:0'>1876</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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  </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'>1328</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/2ttmuio7/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 @nvidia's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/3o1omu9g) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/3o1omu9g/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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  [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
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+ <!--- random size file -->