huggingartists

README.md

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     <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div>
@@ -45,15 +45,15 @@ from datasets import load_dataset
 dataset = load_dataset("huggingartists/adele")
 ```
 
-[Explore the data](https://wandb.ai/huggingartists/huggingartists/runs/wmvp6oou/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/huggingartists/huggingartists/runs/1yyqw6ss/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 Adele's lyrics.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/huggingartists/huggingartists/runs/3hy3u8s4) for full transparency and reproducibility.
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/huggingartists/huggingartists/runs/3qruwjpr) for full transparency and reproducibility.
 
-At the end of training, [the final model](https://wandb.ai/huggingartists/huggingartists/runs/3hy3u8s4/artifacts) is logged and versioned.
+At the end of training, [the final model](https://wandb.ai/huggingartists/huggingartists/runs/3qruwjpr/artifacts) is logged and versioned.
 
 ## How to use
 

config.json

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 {
-  "_name_or_path": "gpt2",
+  "_name_or_path": "huggingartists/adele",
   "activation_function": "gelu_new",
   "architectures": [
     "GPT2LMHeadModel"
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     }
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   "torch_dtype": "float32",
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   "use_cache": true,
   "vocab_size": 50257
 }

evaluation.txt

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optimizer.pt

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pytorch_model.bin

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rng_state.pth

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scheduler.pt

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tokenizer_config.json

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trainer_state.json

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 }

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