multimodalart HF staff commited on
Commit
e9b30e4
1 Parent(s): fd92630

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +2 -4
app.py CHANGED
@@ -324,8 +324,7 @@ def calculate_price(iterations):
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  cost_per_second = 1.05/60/60
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  cost = round(cost_per_second * total_seconds, 2)
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  return f'''To train this LoRA, we will duplicate the space and hook an A10G GPU under the hood.
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- ## Estimated to cost <b>< US$ {str(cost)}</b> with your current train settings <small>({int(iterations)} iterations at 3.50s/it in Spaces A10G at US$1.05/h)</small>
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- #### To continue, grab you <b>write</b> token [here](https://huggingface.co/settings/tokens) and enter it below ↓'''
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  def start_training_og(
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  lora_name,
@@ -835,11 +834,10 @@ with gr.Blocks(css=css, theme=theme) as demo:
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  output_components.insert(1, cost_estimation)
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  gr.on(
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  triggers=[
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- #token.change,
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  payment_setup.click
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  ],
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  fn=check_token,
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- #inputs=token,
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  outputs=[no_payment_method, start],
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  concurrency_limit=50
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  )
 
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  cost_per_second = 1.05/60/60
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  cost = round(cost_per_second * total_seconds, 2)
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  return f'''To train this LoRA, we will duplicate the space and hook an A10G GPU under the hood.
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+ ## Estimated to cost <b>< US$ {str(cost)}</b> for {round(int(total_seconds)/60, 2)} minutes with your current train settings <small>({int(iterations)} iterations at 3.50s/it)</small>'''
 
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  def start_training_og(
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  lora_name,
 
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  output_components.insert(1, cost_estimation)
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  gr.on(
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  triggers=[
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+ images.upload,
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  payment_setup.click
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  ],
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  fn=check_token,
 
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  outputs=[no_payment_method, start],
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  concurrency_limit=50
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  )