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update model card README.md
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README.md
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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#
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```python
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from transformers import pipeline
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prompter = pipeline('text-generation',model='pearsonkyle/ArtPrompter', tokenizer='gpt2')
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texts = prompter('A portal to a galaxy, view with', max_length=30, num_return_sequences=5)
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for i in range(5):
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print(texts[i]['generated_text']+'\n')
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```
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## Intended uses & limitations
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[](https://discord.gg/3S8Taqa2Xy)
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##
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- *The entire universe is a simulation,a confessional with a smiling guy fawkes mask, symmetrical, inviting,hyper realistic*
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- *a pug disguised as a teacher. Setting is a class room*
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- *I wish I had an angel For one moment of love I wish I had your angel Your Virgin Mary undone Im in love with my desire Burning angelwings to dust*
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- *The heart of a galaxy, surrounded by stars, magnetic fields, big bang, cinestill 800T,black background, hyper detail, 8k, black*
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## Training procedure
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~48 hour of finetune on RTX2080 with 212K unique prompts
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Framework versions
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- Transformers 4.
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- Pytorch 1.13.1
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- Tokenizers 0.13.2
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ArtPrompter
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1
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- Tokenizers 0.13.2
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