Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
53f0290
1
Parent(s):
d806dcd
add progress bar
Browse files
app.py
CHANGED
@@ -2,8 +2,7 @@ import gradio as gr
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import polars as pl
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from gradio_huggingfacehub_search import HuggingfaceHubSearch
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import torch
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-
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# import spaces
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from torch import nn
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from transformers import AutoModel, AutoTokenizer, AutoConfig
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from huggingface_hub import PyTorchModelHubMixin
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@@ -33,7 +32,7 @@ model = QualityModel.from_pretrained("nvidia/quality-classifier-deberta").to(dev
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model.eval()
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-
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def predict(texts: list[str]):
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inputs = tokenizer(
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texts, return_tensors="pt", padding="longest", truncation=True
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@@ -112,7 +111,7 @@ with gr.Blocks() as demo:
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return gr.HTML(value=html_code)
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text_column = gr.Textbox(placeholder="text", label="Text colum name to check (data must be non-nested, raw texts!)")
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batch_size = gr.Slider(0, 128, 64, step=8, label="
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num_examples = gr.Number(1000, label="Number of first examples to check")
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gr_check_btn = gr.Button("Check Dataset")
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progress_bar = gr.Label(show_label=False)
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import polars as pl
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from gradio_huggingfacehub_search import HuggingfaceHubSearch
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import torch
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import spaces
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from torch import nn
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from transformers import AutoModel, AutoTokenizer, AutoConfig
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from huggingface_hub import PyTorchModelHubMixin
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model.eval()
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@spaces.GPU
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def predict(texts: list[str]):
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inputs = tokenizer(
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texts, return_tensors="pt", padding="longest", truncation=True
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return gr.HTML(value=html_code)
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text_column = gr.Textbox(placeholder="text", label="Text colum name to check (data must be non-nested, raw texts!)")
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batch_size = gr.Slider(0, 128, 64, step=8, label="Inference batch size (set this to smaller value if this space crashes.)")
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num_examples = gr.Number(1000, label="Number of first examples to check")
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gr_check_btn = gr.Button("Check Dataset")
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progress_bar = gr.Label(show_label=False)
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