Instructions to use HasinMDG/SetFit_Labse_Sentiment_Towards_Topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HasinMDG/SetFit_Labse_Sentiment_Towards_Topic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HasinMDG/SetFit_Labse_Sentiment_Towards_Topic") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39a58a19e09a2da01a4ae759a127092710f0f628167b32c76bdc2acf5771352d
- Size of remote file:
- 10.9 kB
- SHA256:
- 6a5e66b086034e88b091d3b755a8197f2441af696664c0d74a8d8d916a0b7851
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