Instructions to use Kushalguptaiitb/table_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kushalguptaiitb/table_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Kushalguptaiitb/table_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Kushalguptaiitb/table_test") model = AutoModelForObjectDetection.from_pretrained("Kushalguptaiitb/table_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Delete rabbit_mq_config_latest.py
Browse files- rabbit_mq_config_latest.py +0 -20
rabbit_mq_config_latest.py
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import os
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# RabbitMQ connection configuration
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RABBITMQ = {
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"HOST": os.getenv("RABBITMQ_HOST", "10.221.162.2"),
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"PORT": int(os.getenv("RABBITMQ_PORT", 5672)),
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"VIRTUAL_HOST": os.getenv("RABBITMQ_VHOST", "/"),
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"USERNAME": os.getenv("RABBITMQ_USER", "iqeq"),
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"PASSWORD": os.getenv("RABBITMQ_PASS", "Wissen@123"),
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# Exchange settings
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"EXCHANGE_NAME": os.getenv("RABBITMQ_EXCHANGE", "priority_topic_exchange"),
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"EXCHANGE_TYPE": os.getenv("RABBITMQ_EXCHANGE_TYPE", "topic"),
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# Queue names
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"QUEUES": {
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"RESPONSE_QUEUE": os.getenv("RESPONSE_QUEUE", "IQEQ_Response")
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}
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}
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