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Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: Pongsasit Thongpramoon
- Model type: Cross Encoder
- Language(s) (NLP): Thai
How to Get Started with the Model
Use the code below to get started with the model.
from sentence_transformers.cross_encoder import CrossEncoder
model = CrossEncoder("Pongsasit/mod-th-cross-encoder")
scores = model.predict([["อาหารตามสั่ง", "หมู เห็ด เป็ด ไก่"], ["อาหารตามสั่ง", "รถ เรือ เครื่องบิน จักรยาน"]])
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from sentence_transformers import CrossEncoder model = CrossEncoder("Pongsasit/mod-th-cross-encoder") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores)