boris commited on
Commit
8e004bc
1 Parent(s): 7e24ebf

New model from https://wandb.ai/wandb/huggingtweets/runs/1qr2itgh

Browse files
README.md CHANGED
@@ -1,17 +1,27 @@
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  ---
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  language: en
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- thumbnail: https://www.huggingtweets.com/daltonsakthi/1616690964327/predictions.png
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  tags:
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  - huggingtweets
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  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('https://pbs.twimg.com/profile_images/1203851650215137286/Sjc-cYb8_400x400.jpg')">
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- </div>
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- <div style="margin-top: 8px; font-size: 19px; font-weight: 800">Dalton AR Sakthivadivel 🤖 AI Bot </div>
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- <div style="font-size: 15px">@daltonsakthi bot</div>
 
 
 
 
 
 
 
 
 
 
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  </div>
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  I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
@@ -28,24 +38,24 @@ To understand how the model was developed, check the [W&B report](https://wandb.
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  ## Training data
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- The model was trained on [@daltonsakthi's tweets](https://twitter.com/daltonsakthi).
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- | Data | Quantity |
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  | --- | --- |
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- | Tweets downloaded | 2614 |
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- | Retweets | 1470 |
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- | Short tweets | 61 |
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- | Tweets kept | 1083 |
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- [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/bsjk833r/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 @daltonsakthi's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2ahbugci) for full transparency and reproducibility.
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- At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2ahbugci/artifacts) is logged and versioned.
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  ## How to use
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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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  - text: "My dream is"
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  ---
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+ <div class="inline-flex flex-col" style="line-height: 1.5;">
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+ <div class="flex">
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+ <div
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+ style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1203851650215137286/Sjc-cYb8_400x400.jpg&#39;)">
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+ </div>
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+ <div
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+ style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)">
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+ </div>
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+ <div
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+ style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)">
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+ </div>
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+ </div>
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+ <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
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+ <div style="text-align: center; font-size: 16px; font-weight: 800">Dalton AR Sakthivadivel</div>
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+ <div style="text-align: center; font-size: 14px;">@daltonsakthi</div>
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  </div>
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  I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
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  ## Training data
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+ The model was trained on tweets from Dalton AR Sakthivadivel.
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+ | Data | Dalton AR Sakthivadivel |
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  | --- | --- |
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+ | Tweets downloaded | 3220 |
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+ | Retweets | 1653 |
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+ | Short tweets | 71 |
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+ | Tweets kept | 1496 |
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+ [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/aqk1rdls/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 @daltonsakthi's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1qr2itgh) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1qr2itgh/artifacts) is logged and versioned.
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  ## How to use
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config.json CHANGED
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  "use_cache": true,
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  "vocab_size": 50257
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