Instructions to use YakovElm/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/test") 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 YakovElm/test with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/test") 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 YakovElm/test: direct link, hf CLI and curl.
- Browser
- Download file 324 Bytes
-
https://huggingface.co/YakovElm/test/resolve/main/model_head.pkl
- Command line
-
hf download hf://YakovElm/test/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/YakovElm/test/resolve/main/model_head.pkl
324 Bytes
- Xet hash:
- c45b9a9befbdff29d0184d56a388d750eb0499f2d0b4f22223f1c3cc36acffbd
- Size of remote file:
- 324 Bytes
- SHA256:
- 95a2349eb3f96eb70d9185b2f02af4ffabe28566b0bbeda0ad56312e9e6879cb
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