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ZeroCommand
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Commit
•
2f7dd9a
1
Parent(s):
79d13cd
check if config submitted path exist
Browse files- app_debug.py +3 -1
- text_classification.py +1 -1
- text_classification_ui_helpers.py +2 -1
app_debug.py
CHANGED
@@ -3,7 +3,7 @@ from os.path import isfile, join
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import html
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import gradio as gr
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-
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import pipe
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from io_utils import get_logs_file
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@@ -69,6 +69,8 @@ def get_queue_status():
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def get_demo():
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with gr.Row():
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gr.HTML(
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value=get_queue_status,
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import html
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import gradio as gr
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+
import os
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import pipe
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from io_utils import get_logs_file
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def get_demo():
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if not os.path.exists(CONFIG_PATH):
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os.makedirs(CONFIG_PATH)
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with gr.Row():
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gr.HTML(
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value=get_queue_status,
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text_classification.py
CHANGED
@@ -7,9 +7,9 @@ import pandas as pd
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from transformers import pipeline
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import requests
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import os
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logger = logging.getLogger(__name__)
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HF_WRITE_TOKEN = "HF_WRITE_TOKEN"
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AUTH_CHECK_URL = "https://huggingface.co/api/whoami-v2"
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logger = logging.getLogger(__file__)
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from transformers import pipeline
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import requests
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import os
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from app_env import HF_WRITE_TOKEN
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logger = logging.getLogger(__name__)
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AUTH_CHECK_URL = "https://huggingface.co/api/whoami-v2"
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logger = logging.getLogger(__file__)
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text_classification_ui_helpers.py
CHANGED
@@ -35,6 +35,7 @@ from wordings import (
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get_dataset_fetch_error_raw,
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)
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import os
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MAX_LABELS = 40
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MAX_FEATURES = 20
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@@ -268,7 +269,7 @@ def align_columns_and_show_prediction(
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gr.Dropdown(visible=False) for _ in range(MAX_LABELS + MAX_FEATURES)
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]
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-
hf_token = os.environ.get(
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prediction_input, prediction_response = get_example_prediction(
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model_id, dataset_id, dataset_config, dataset_split, hf_token
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get_dataset_fetch_error_raw,
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)
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import os
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from app_env import HF_WRITE_TOKEN
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MAX_LABELS = 40
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MAX_FEATURES = 20
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gr.Dropdown(visible=False) for _ in range(MAX_LABELS + MAX_FEATURES)
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]
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hf_token = os.environ.get(HF_WRITE_TOKEN, default="")
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prediction_input, prediction_response = get_example_prediction(
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model_id, dataset_id, dataset_config, dataset_split, hf_token
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