Sentence Similarity
sentence-transformers
PyTorch
Transformers
camembert
feature-extraction
text-embeddings-inference
Instructions to use kornwtp/simcse-model-wangchanberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kornwtp/simcse-model-wangchanberta with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kornwtp/simcse-model-wangchanberta") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use kornwtp/simcse-model-wangchanberta with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kornwtp/simcse-model-wangchanberta") model = AutoModel.from_pretrained("kornwtp/simcse-model-wangchanberta") - Notebooks
- Google Colab
- Kaggle
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README.md
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```python
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from sentence_transformers import SentenceTransformer
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sentences = ["
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model = SentenceTransformer('{MODEL_NAME}')
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embeddings = model.encode(sentences)
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```python
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from sentence_transformers import SentenceTransformer
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sentences = ["กลุ่มผู้ชายเล่นฟุตบอลบนชายหาด", "กลุ่มเด็กชายกำลังเล่นฟุตบอลบนชายหาด"]
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model = SentenceTransformer('{MODEL_NAME}')
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embeddings = model.encode(sentences)
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