Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use Tempo14/parameter-mini-lds_cpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Tempo14/parameter-mini-lds_cpu with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Tempo14/parameter-mini-lds_cpu") - sentence-transformers
How to use Tempo14/parameter-mini-lds_cpu with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Tempo14/parameter-mini-lds_cpu") 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:
- be6a338b92e1964d4be033d9676cf2cff45893ddfb8d207a9cc89e7376e022ce
- Size of remote file:
- 3.94 kB
- SHA256:
- ceea35606378f0c0e81dd81266bdf2d79f57362fd84e2208c7ded8462b9e1d9f
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