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
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f15aa0a66cb9a5842ace9a51f60621b26b4ad85734ef4769dcf7108094d06a40
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size 532299592
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