Instructions to use ilhkn/proj_2_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ilhkn/proj_2_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ilhkn/proj_2_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] - setfit
How to use ilhkn/proj_2_model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ilhkn/proj_2_model") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from ilhkn/proj_2_model: direct link, hf CLI and curl.
- Browser
- Download file 56.3 kB
-
https://huggingface.co/ilhkn/proj_2_model/resolve/main/model_head.pkl
- Command line
-
hf download hf://ilhkn/proj_2_model/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/ilhkn/proj_2_model/resolve/main/model_head.pkl
56.3 kB
- Xet hash:
- db4c21dba25a35a0f188ca2b015c4c48a0b60d4f4134bdd2d6e6aeb168a51709
- Size of remote file:
- 56.3 kB
- SHA256:
- aadb27a681f0965953bf45ba93e0d7a0402333f24f8b3b9ed6504c807218592b
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