Sentence Similarity
sentence-transformers
PyTorch
Transformers
roberta
feature-extraction
text-embeddings-inference
Instructions to use api19750904/efeverde-cat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use api19750904/efeverde-cat with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("api19750904/efeverde-cat") 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 api19750904/efeverde-cat with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("api19750904/efeverde-cat") model = AutoModel.from_pretrained("api19750904/efeverde-cat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce2173c6d46df303efa71158091bfb1eec9a7c5a569beb6763c09959ff58355a
- Size of remote file:
- 499 MB
- SHA256:
- 0c4455639e6d680d535bdebc970ef303aa9187890605a7e0a2bdeb42ac7402cf
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