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:
- 22aa723f668c5d387230614562643f11000563ab48e028080d586ac4c916e7b2
- Size of remote file:
- 1.88 GB
- SHA256:
- 716d150f23f3f6132cbfe538d26a86fa4a25b1e68ec5eaeb0ccf5d5c0bdc34d8
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