Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use kowshikBlue/dummy_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kowshikBlue/dummy_1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kowshikBlue/dummy_1") 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 kowshikBlue/dummy_1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kowshikBlue/dummy_1") model = AutoModel.from_pretrained("kowshikBlue/dummy_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50d1bb2c074dec39ac5bc438a27d0f436fb81ab307de19d5baea60ae5c26d3a3
- Size of remote file:
- 6.96 kB
- SHA256:
- a93169d3a451e5b0333e1984b55770c459a08beca55e771e18499a8446da6e16
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