Jyotiyadav commited on
Commit
3d4db42
1 Parent(s): be95230

Update app.py

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Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -3,7 +3,7 @@ from transformers import T5ForConditionalGeneration, T5Tokenizer
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  from textwrap import fill
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  # Load fine-tuned model and tokenizer
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- last_checkpoint = "Jyotiyadav/FLANT-5_Model_Forecasting2"
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  finetuned_model = T5ForConditionalGeneration.from_pretrained(last_checkpoint)
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  tokenizer = T5Tokenizer.from_pretrained(last_checkpoint)
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@@ -28,10 +28,10 @@ iface = gr.Interface(
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  title="Question Answering with T5 Model",
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  description="Enter your question to get the answer.",
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  examples=[
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- ["On 2013-02-11, at store number 1 in Quito, Pichincha, under store type D and cluster 13, with 396 transactions recorded, and crude oil price at 97.01, what was the sales quantity of BABY CARE products (ID: 73063), considering whether they were on promotion (On Promotion: 0) in Ecuador during Carnaval (Transferred: False)?"],
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- ["On 2013-02-11, at store number 10 in Quito, Pichincha, under store type C and cluster 15, with 823 transactions recorded, and crude oil price at 97.01, what was the sales quantity of MEATS products (ID: 73119), considering whether they were on promotion (On Promotion: 0) in Ecuador during Carnaval (Transferred: False)?"],
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- ["On 2013-02-11, at store number 10 in Quito, Pichincha, under store type C and cluster 15, with 823 transactions recorded, and crude oil price at 97.01, what was the sales quantity of FROZEN FOODS products (ID: 73106), considering whether they were on promotion (On Promotion: 0) in Ecuador during Carnaval (Transferred: False)?"],
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- ["On 2013-02-11, at store number 10 in Quito, Pichincha, under store type C and cluster 15, with 823 transactions recorded, and crude oil price at 97.01, what was the sales quantity of CLEANING products (ID: 73102), considering whether they were on promotion (On Promotion: 0) in Ecuador during Carnaval (Transferred: False)?"]
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  ]
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  )
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  from textwrap import fill
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  # Load fine-tuned model and tokenizer
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+ last_checkpoint = "Jyotiyadav/model2.0"
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  finetuned_model = T5ForConditionalGeneration.from_pretrained(last_checkpoint)
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  tokenizer = T5Tokenizer.from_pretrained(last_checkpoint)
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  title="Question Answering with T5 Model",
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  description="Enter your question to get the answer.",
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  examples=[
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+ ["For store number 1 in the city of Quito, with products from various categories such as AUTOMOTIVE, during a 0 on 2017-8-16, with no, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"],
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+ ["For store number 1 in the city of Quito, with products from various categories such as BABY CARE, during a 0 on 2017-8-16, with no, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"],
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+ ["For store number 1 in the city of Quito, with products from various categories such as BEAUTY, during a 0 on 2017-8-16, with promotions, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"],
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+ ["For store number 1 in the city of Quito, with products from various categories such as HOME CARE, during a 0 on 2017-8-16, with promotions, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"]
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  ]
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  )
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