Instructions to use pkshatech/simcse-ja-bert-base-clcmlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pkshatech/simcse-ja-bert-base-clcmlp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pkshatech/simcse-ja-bert-base-clcmlp") sentences = [ "This widget can't work correctly now.", "Sorry :(", "Try this model in your local environment!" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use pkshatech/simcse-ja-bert-base-clcmlp with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pkshatech/simcse-ja-bert-base-clcmlp") model = AutoModel.from_pretrained("pkshatech/simcse-ja-bert-base-clcmlp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
modified typo
Browse files- README_JA.md +1 -1
README_JA.md
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@@ -25,7 +25,7 @@ sentences = [
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"広目天は、仏教における四天王の一尊であり、サンスクリット語の「種々の眼をした者」を名前の由来とする。",
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]
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model = SentenceTransformer('
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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"広目天は、仏教における四天王の一尊であり、サンスクリット語の「種々の眼をした者」を名前の由来とする。",
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]
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model = SentenceTransformer('pkshatech/simcse-ja-bert-base-clcmlp')
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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