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iopred

Text Generation
Transformers
PyTorch
English
gpt2
huggingtweets
text-generation-inference
Model card Files
xet
 Community
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boris commited on
Commit
a7ff1fd
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1 Parent(s): 4dbda19

New model from https://wandb.ai/wandb/huggingtweets/runs/2i464eff

Browse files
Files changed (3) hide show
  1. README.md +9 -9
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ widget:
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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">kit</div>
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  <div style="text-align: center; font-size: 14px;">@iopred</div>
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  </div>
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@@ -38,24 +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 tweets from kit.
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- | Data | kit |
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  | --- | --- |
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  | Tweets downloaded | 3240 |
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- | Retweets | 180 |
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- | Short tweets | 260 |
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- | Tweets kept | 2800 |
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- [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1p6o3x33/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 @iopred's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3dve0xrl) for full transparency and reproducibility.
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- At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3dve0xrl/artifacts) is logged and versioned.
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  ## How to use
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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">diet dr. kit</div>
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  <div style="text-align: center; font-size: 14px;">@iopred</div>
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  </div>
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  ## Training data
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+ The model was trained on tweets from diet dr. kit.
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+ | Data | diet dr. kit |
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  | --- | --- |
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  | Tweets downloaded | 3240 |
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+ | Retweets | 177 |
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+ | Short tweets | 258 |
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+ | Tweets kept | 2805 |
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+ [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/52vmud4n/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 @iopred's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2i464eff) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2i464eff/artifacts) is logged and versioned.
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  ## How to use
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