Sentence Similarity
sentence-transformers
Safetensors
Transformers
roberta
feature-extraction
text-embeddings-inference
Instructions to use nanalysenko/model-test-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nanalysenko/model-test-3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nanalysenko/model-test-3") 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 nanalysenko/model-test-3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nanalysenko/model-test-3") model = AutoModel.from_pretrained("nanalysenko/model-test-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46128f91d1a94a92a53ef930fa4bab94cc69103ded5505d3fa9eb288b5044281
- Size of remote file:
- 328 MB
- SHA256:
- f21e05e1e3a1c2cd6c5c6f28a709595e66267098b991998464b5da5a231f042e
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