Instructions to use TranVanTri352/MCQ_Paragraph_AI_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TranVanTri352/MCQ_Paragraph_AI_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="TranVanTri352/MCQ_Paragraph_AI_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("TranVanTri352/MCQ_Paragraph_AI_Model") model = AutoModelForSeq2SeqLM.from_pretrained("TranVanTri352/MCQ_Paragraph_AI_Model") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -70,7 +70,7 @@ model = T5ForConditionalGeneration.from_pretrained(model_name, from_tf=True)
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@app.route('/status', methods=['GET'])
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def model_status():
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try:
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if model and tokenizer:
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return jsonify({
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'status': 'ready',
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@app.route('/status', methods=['GET'])
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def model_status():
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try:
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# Check if the model is loaded
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if model and tokenizer:
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return jsonify({
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'status': 'ready',
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