Sentence Similarity
sentence-transformers
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use Youmnaaaa/Semantic-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Youmnaaaa/Semantic-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Youmnaaaa/Semantic-model") 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 Youmnaaaa/Semantic-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Youmnaaaa/Semantic-model") model = AutoModel.from_pretrained("Youmnaaaa/Semantic-model") - Notebooks
- Google Colab
- Kaggle
Upload model/config_sentence_transformers.json with huggingface_hub
Browse files
model/config_sentence_transformers.json
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{
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"__version__": {
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"sentence_transformers": "5.3.0",
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"transformers": "5.0.0",
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"pytorch": "2.10.0+cpu"
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},
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"model_type": "SentenceTransformer",
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"prompts": {
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"query": "",
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"document": ""
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},
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"default_prompt_name": null,
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"similarity_fn_name": "cosine"
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}
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