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@@ -7,6 +7,17 @@ widget:
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  - text: "My dream is"
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  ---
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  <div>
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  <div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('http://pbs.twimg.com/profile_images/573383872/img_0621_400x400.jpg')">
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  </div>
@@ -30,35 +41,56 @@ To understand how the model was developed, check the [W&B report](https://bit.ly
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  The model was trained on [@l2k's tweets](https://twitter.com/l2k).
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- | Data | Quantity |
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- |-------------------|--------------|
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- | Tweets downloaded | 2541 |
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- | Retweets | 578 |
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- | Short tweets | 87 |
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- | Tweets kept | 1876 |
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-
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- [Explore the data](https://app.wandb.ai/wandb/huggingtweets-dev/runs/18jzfgqc/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 @l2k's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets-dev/runs/2ly0pm0j) for full transparency and reproducibility.
 
 
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  ## Intended uses & limitations
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- #### How to use
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  You can use this model directly with a pipeline for text generation:
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- ```python
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- from transformers import pipeline
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- generator = pipeline('text-generation',
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- model='huggingtweets/l2k')
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- generator("My dream is", max_length=50, num_return_sequences=5)
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- ```
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- #### Limitations and bias
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  The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
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@@ -68,8 +100,12 @@ In addition, the data present in the user's tweets further affects the text gene
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  *Built by Boris Dayma*
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  [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/borisdayma)
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  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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  - text: "My dream is"
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  ---
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+ <link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
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+
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+ <style>
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+ @media (prefers-color-scheme: dark) {
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+ .prose { color: #E2E8F0 !important; }
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+ .prose h2, .prose h3, .prose a, .prose thead { color: #F7FAFC !important; }
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+ }
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+ </style>
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+
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+ <section class='prose'>
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+
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  <div>
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  <div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('http://pbs.twimg.com/profile_images/573383872/img_0621_400x400.jpg')">
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  </div>
 
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  The model was trained on [@l2k's tweets](https://twitter.com/l2k).
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+ <table style='border-width:0'>
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+ <thead style='border-width:0'>
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+ <tr style='border-width:0 0 1px 0; border-color: #CBD5E0'>
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+ <th style='border-width:0'>Data</th>
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+ <th style='border-width:0'>Quantity</th>
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+ </tr>
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+ </thead>
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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'>2569</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'>594</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'>87</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'>1888</td>
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+ </tr>
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+ </tbody>
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+ </table>
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+
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+ [Explore the data](https://app.wandb.ai/wandb/huggingtweets-dev/runs/27nq9kzg/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 @l2k's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets-dev/runs/6edmz7mo) for full transparency and reproducibility.
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+
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+ At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets-dev/runs/6edmz7mo/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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+ ### How to use
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  You can use this model directly with a pipeline for text generation:
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+ <pre><code><span style="color:#03A9F4">from</span> transformers <span style="color:#03A9F4">import</span> pipeline
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+ generator = pipeline(<span style="color:#FF9800">'text-generation'</span>,
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+ model=<span style="color:#FF9800">'huggingtweets/l2k'</span>)
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+ generator(<span style="color:#FF9800">"My dream is"</span>, num_return_sequences=<span style="color:#8BC34A">5</span>)</code></pre>
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+
 
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+ ### Limitations and bias
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  The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
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  *Built by Boris Dayma*
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+ </section>
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+
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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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+ </section>
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  [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)