update model card README.md

README.md

@@ -10,52 +10,24 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# [ArtPrompter](https://pearsonkyle.github.io/Art-Prompter/)
+# ArtPrompter
 
-A [gpt2](https://huggingface.co/gpt2) powered predictive keyboard for making descriptive text prompts for A.I. image generators (e.g. MidJourney, Stable Diffusion, ArtBot, etc). The model was trained on a custom dataset containing 521K MidJourney images corresponding to 212K unique prompts.
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
 
-```python
-from transformers import pipeline
-
-ai = pipeline('text-generation',model='pearsonkyle/ArtPrompter', tokenizer='gpt2')
-
-texts = ai('The', max_length=30, num_return_sequences=5)
-
-for i in range(5):
-    print(texts[i]['generated_text']+'\n')
-```
-
-[![Art Prompter](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1HQOtD2LENTeXEaxHUfIhDKUaPIGd6oTR?usp=sharing)
+## Model description
 
+More information needed
 
 ## Intended uses & limitations
 
-Build prompts and generate images on Discord!
-
-
-[![](https://cincydiscord.com/wp-content/uploads/2019/02/CINCYDISCORDJOIN.png)](https://discord.gg/3S8Taqa2Xy)
-
-
-[![](https://pearsonkyle.github.io/Art-Prompter/images/discord_bot.png)](https://discord.gg/3S8Taqa2Xy)
-
+More information needed
 
-## Examples
-
-All text prompts below are generated with our language model
-
-- *The entire universe is a simulation,a confessional with a smiling guy fawkes mask, symmetrical, inviting,hyper realistic* 
-
-- *a pug disguised as a teacher. Setting is a class room*
-
-- *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*
-
-- *The heart of a galaxy, surrounded by stars, magnetic fields, big bang, cinestill 800T,black background, hyper detail, 8k, black*
+## Training and evaluation data
 
+More information needed
 
 ## Training procedure
 
-~30 hour of finetune on RTX2080 with 212K unique prompts
-
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -67,8 +39,12 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 50
 
+### Training results
+
+
+
 ### Framework versions
 
 - Transformers 4.25.1
 - Pytorch 1.13.1
-- Tokenizers 0.13.2
+- Tokenizers 0.13.2