Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use Karmukilan/information-content-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Karmukilan/information-content-model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Karmukilan/information-content-model") - sentence-transformers
How to use Karmukilan/information-content-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Karmukilan/information-content-model") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- accdac93503c466d8e52c3b2499bbfe6c109009b42b461505a05ac9f1f1127c3
- Size of remote file:
- 7.01 kB
- SHA256:
- dcd39ea058b6ecd497403855481b67dfab4984a0622153472681ad094bf2774b
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