Instructions to use pkshatech/GLuCoSE-base-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pkshatech/GLuCoSE-base-ja with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pkshatech/GLuCoSE-base-ja") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use pkshatech/GLuCoSE-base-ja with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pkshatech/GLuCoSE-base-ja") model = AutoModel.from_pretrained("pkshatech/GLuCoSE-base-ja") - Notebooks
- Google Colab
- Kaggle
Update base model name
#3
by meguruin - opened
README.md
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- MoritzLaurer/multilingual-NLI-26lang-2mil7
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- castorini/mr-tydi
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- hpprc/jsick
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base_model:
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- MoritzLaurer/multilingual-NLI-26lang-2mil7
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- castorini/mr-tydi
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- hpprc/jsick
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base_model:
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- studio-ousia/luke-japanese-base-lite
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