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--- |
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library_name: transformers |
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tags: [] |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** Pongsasit Thongpramoon |
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- **Model type:** Cross Encoder |
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- **Language(s) (NLP):** Thai |
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- **Finetuned from model:** cross-encoder/ms-marco-MiniLM-L-12-v2 |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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```python |
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from sentence_transformers.cross_encoder import CrossEncoder |
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model = CrossEncoder("Pongsasit/mod-th-cross-encoder-minilm") |
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th_question = "การใช้สีส่งผลต่ออารมณ์ของภาพวาดอย่างไร" |
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th_answer1 = "เมื่อศิลปินเลือกเฉดสีที่แตกต่างกัน มันก็เหมือนกับการเลือกความรู้สึกที่แตกต่างกันให้กับภาพของพวกเขา!" |
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th_answer2 = "ทำไมสิ่งเล็กๆ น้อยๆ บางครั้งจึงดูเหมือนอยู่สองแห่งในเวลาเดียวกัน? เหมือนพยายามจับผีเล่นซ่อนหา!" |
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en_question = "How does the use of color contribute to the emotional impact of a painting?" |
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en_answer1 = "When an artist picks different shades, it's like picking different feelings for their picture!" |
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en_answer2 = "Why do really tiny things sometimes seem to be in two places at the same time? It's like trying to catch a sneaky ghost playing hide and seek!" |
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th_scores = model.predict([[th_question, th_answer1], [th_question, th_answer2]]) |
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en_scores = model.predict([[en_question, en_answer1], [en_question, en_answer2]]) |
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``` |
