Berbex commited on
Commit
33649cd
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1 Parent(s): c3b69c6

Update app.py

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Files changed (1) hide show
  1. app.py +12 -9
app.py CHANGED
@@ -1,5 +1,14 @@
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  #!pip install -q transformers datasets torch gradio console_logging numpy
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  import gradio as gr
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  title = 'Text market sentiment'
@@ -8,21 +17,15 @@ model = torch.load("huggingface/Berbex/Model")
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  inp = [gr.Textbox(label='API Key', placeholder="What is your API Key?"), gr.Textbox(label='Audio File URL', placeholder="Audio file URL?")]
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  out = gr.Textbox(label='Output')
 
 
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  interface = gr.Interface.load(input=inp,output=out,
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  title = title,
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  theme = "peach",
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  examples = [[text_]]).launch()
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- import torch
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- from datasets import load_dataset
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- from console_logging.console import Console
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- import numpy as np
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- from transformers import AutoModelForSequenceClassification, AutoTokenizer
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- from transformers import TrainingArguments, Trainer
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- from sklearn.metrics import f1_score, roc_auc_score, accuracy_score
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- from transformers import EvalPrediction
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- import torch
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  console = Console()
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  dataset = load_dataset("zeroshot/twitter-financial-news-sentiment", )
 
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  #!pip install -q transformers datasets torch gradio console_logging numpy
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+ import torch
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+ from datasets import load_dataset
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+ from console_logging.console import Console
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+ import numpy as np
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+ from transformers import AutoModelForSequenceClassification, AutoTokenizer
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+ from transformers import TrainingArguments, Trainer
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+ from sklearn.metrics import f1_score, roc_auc_score, accuracy_score
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+ from transformers import EvalPrediction
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+ import torch
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  import gradio as gr
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  title = 'Text market sentiment'
 
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  inp = [gr.Textbox(label='API Key', placeholder="What is your API Key?"), gr.Textbox(label='Audio File URL', placeholder="Audio file URL?")]
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  out = gr.Textbox(label='Output')
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+ text_button = gr.Button("Flip")
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+ text_button.click(audio_to_text, inputs=inp, outputs=out)
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  interface = gr.Interface.load(input=inp,output=out,
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  title = title,
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  theme = "peach",
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  examples = [[text_]]).launch()
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+
 
 
 
 
 
 
 
 
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  console = Console()
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  dataset = load_dataset("zeroshot/twitter-financial-news-sentiment", )