Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use BlueAvenir/TestDummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BlueAvenir/TestDummy with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BlueAvenir/TestDummy") 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 BlueAvenir/TestDummy with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BlueAvenir/TestDummy") model = AutoModel.from_pretrained("BlueAvenir/TestDummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55a4cdda9ba38793e11b21a739746692b2ed4cd117ebc38c765377095e3eedb5
- Size of remote file:
- 1.11 GB
- SHA256:
- 6b0eb155dbb676158aa380ecb74292708e5f7b9ae752158bc461fb4421a29ee4
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