Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use gnail/hamlet-distill-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gnail/hamlet-distill-st with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gnail/hamlet-distill-st") 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 gnail/hamlet-distill-st with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gnail/hamlet-distill-st") model = AutoModel.from_pretrained("gnail/hamlet-distill-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39fb3e5faffa5a1663d0b2415c5ae28b2b5f8eb598bea09571405a1fdfb998f6
- Size of remote file:
- 1.11 GB
- SHA256:
- 2c6ddb3f5b4f8731cd33268c6dd350cf227ea4008b678cd29f712e213d1e0721
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