Instructions to use yjlee1011/ncodeR_data_multilabel_16samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yjlee1011/ncodeR_data_multilabel_16samples with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yjlee1011/ncodeR_data_multilabel_16samples") 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] - setfit
How to use yjlee1011/ncodeR_data_multilabel_16samples with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("yjlee1011/ncodeR_data_multilabel_16samples") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
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