New model from https://wandb.ai/wandb/huggingtweets/runs/xegerdmo

README.md

@@ -47,15 +47,15 @@ The model was trained on tweets from mohamad yazdi.
 | Short tweets | -401 |
 | Tweets kept | 463 |
 
-[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/rrxqoxc5/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
+[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/pfnvvlqn/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 @mohamad_yazdi's tweets.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/22w0j6p9) for full transparency and reproducibility.
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/xegerdmo) for full transparency and reproducibility.
 
-At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/22w0j6p9/artifacts) is logged and versioned.
+At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/xegerdmo/artifacts) is logged and versioned.
 
 ## How to use
 

config.json

@@ -31,6 +31,9 @@
       "do_sample": true,
       "max_length": 160,
       "min_length": 10,
+      "no_repeat_ngram_size": 2,
+      "num_beam_groups": 2,
+      "num_beams": 2,
       "prefix": "<|endoftext|>",
       "temperature": 1.0,
       "top_p": 0.95

pytorch_model.bin

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training_args.bin

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