|
--- |
|
language: en |
|
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo_share.png?raw=true |
|
tags: |
|
- huggingtweets |
|
widget: |
|
- text: "My dream is" |
|
--- |
|
|
|
<div> |
|
<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')"> |
|
</div> |
|
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Lukas Biewald 🤖 AI Bot </div> |
|
<div style="font-size: 15px; color: #657786">@l2k 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://bit.ly/2TGXMZf). |
|
|
|
## Training data |
|
|
|
The model was trained on [@l2k's tweets](https://twitter.com/l2k). |
|
|
|
| Data | Quantity | |
|
|-------------------|--------------| |
|
| Tweets downloaded | 2541 | |
|
| Retweets | 578 | |
|
| Short tweets | 87 | |
|
| Tweets kept | 1876 | |
|
|
|
[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. |
|
|
|
## Training procedure |
|
|
|
The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @l2k's tweets. |
|
|
|
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. |
|
|
|
## Intended uses & limitations |
|
|
|
#### 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/l2k') |
|
generator("My dream is", max_length=50, 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/borisdayma) |
|
|
|
For more details, visit the project repository. |
|
|
|
[](https://github.com/borisdayma/huggingtweets) |
|
|