New model from https://wandb.ai/wandb/huggingtweets/runs/179s3cys

README.md

@@ -1,6 +1,6 @@
 ---
 language: en
-thumbnail: https://www.huggingtweets.com/marknorm/1616032471268/predictions.png
+thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
 tags:
 - huggingtweets
 widget:
@@ -37,15 +37,15 @@ The model was trained on [@marknorm's tweets](https://twitter.com/marknorm).
 | Short tweets | 546 |
 | Tweets kept | 2556 |
 
-[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/28231v8r/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/3iwytwbq/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 @marknorm's tweets.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/ur06e0lk) for full transparency and reproducibility.
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/179s3cys) for full transparency and reproducibility.
 
-At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/ur06e0lk/artifacts) is logged and versioned.
+At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/179s3cys/artifacts) is logged and versioned.
 
 ## How to use
 

config.json

@@ -34,7 +34,7 @@
       "top_p": 0.95
     }
   },
-  "transformers_version": "4.4.1",
+  "transformers_version": "4.4.2",
   "use_cache": true,
   "vocab_size": 50257
 }

pytorch_model.bin

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training_args.bin

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