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README.md
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---
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language: en
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thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/
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tags:
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- huggingtweets
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widget:
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<section class='prose'>
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<div>
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<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('
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</div>
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<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Naval 🤖 AI Bot </div>
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<div style="font-size: 15px; color: #657786">@naval bot</div>
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To understand how the model was developed, check the [W&B report](https://
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## Training data
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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'>
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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'>
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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'>
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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'>
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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/
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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 @naval's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/
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At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/
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## Intended uses & limitations
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</section>
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[](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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</section>
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[](https://github.com/borisdayma/huggingtweets)
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---
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language: en
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thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
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tags:
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- huggingtweets
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widget:
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<section class='prose'>
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<div>
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<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1256841238298292232/ycqwaMI2_400x400.jpg')">
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</div>
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<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Naval 🤖 AI Bot </div>
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<div style="font-size: 15px; color: #657786">@naval bot</div>
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To understand how the model was developed, check the [W&B report](https://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).
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## Training data
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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'>3217</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'>166</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'>638</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'>2413</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/37daadvx/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 @naval's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/bru9kuy8) for full transparency and reproducibility.
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At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/bru9kuy8/artifacts) is logged and versioned.
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## Intended uses & limitations
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</section>
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[](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.
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</section>
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[](https://github.com/borisdayma/huggingtweets)
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