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| --- | |
| language: en | |
| thumbnail: https://www.huggingtweets.com/uhaul_cares/1616885643863/predictions.png | |
| tags: | |
| - huggingtweets | |
| widget: | |
| - text: "My dream is" | |
| --- | |
| <div> | |
| <div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/477228429733941251/1Jv8fSSP_400x400.jpeg')"> | |
| </div> | |
| <div style="margin-top: 8px; font-size: 19px; font-weight: 800">U-Haul Cares 🤖 AI Bot </div> | |
| <div style="font-size: 15px">@uhaul_cares bot</div> | |
| </div> | |
| I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets). | |
| Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)! | |
| ## How does it work? | |
| The model uses the following pipeline. | |
|  | |
| To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI). | |
| ## Training data | |
| The model was trained on [@uhaul_cares's tweets](https://twitter.com/uhaul_cares). | |
| | Data | Quantity | | |
| | --- | --- | | |
| | Tweets downloaded | 3225 | | |
| | Retweets | 9 | | |
| | Short tweets | 5 | | |
| | Tweets kept | 3211 | | |
| [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1s0dgmbq/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline. | |
| ## Training procedure | |
| The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @uhaul_cares's tweets. | |
| Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/192wppwc) for full transparency and reproducibility. | |
| At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/192wppwc/artifacts) is logged and versioned. | |
| ## How to use | |
| You can use this model directly with a pipeline for text generation: | |
| ```python | |
| from transformers import pipeline | |
| generator = pipeline('text-generation', | |
| model='huggingtweets/uhaul_cares') | |
| generator("My dream is", num_return_sequences=5) | |
| ``` | |
| ## Limitations and bias | |
| The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias). | |
| In addition, the data present in the user's tweets further affects the text generated by the model. | |
| ## About | |
| *Built by Boris Dayma* | |
| [](https://twitter.com/intent/follow?screen_name=borisdayma) | |
| For more details, visit the project repository. | |
| [](https://github.com/borisdayma/huggingtweets) | |