Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use Etelis/Sentiment140_fewshot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Etelis/Sentiment140_fewshot with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Etelis/Sentiment140_fewshot") 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 Etelis/Sentiment140_fewshot with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Etelis/Sentiment140_fewshot") model = AutoModel.from_pretrained("Etelis/Sentiment140_fewshot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cac061ec6995b535d2d9cf5ca301c4f433c37739b4c0a29e83e868a7da335ec
- Size of remote file:
- 7.12 kB
- SHA256:
- 7787c55572fdf67ce336111891c4ebee713d7a88b6e692995601fe92ac320089
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