Instructions to use leofn3/modelo_multiclass_teste01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use leofn3/modelo_multiclass_teste01 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("leofn3/modelo_multiclass_teste01") 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 leofn3/modelo_multiclass_teste01 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("leofn3/modelo_multiclass_teste01") 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 leofn3/modelo_multiclass_teste01: direct link, hf CLI and curl.
- Browser
- Download file 3.92 kB
-
https://huggingface.co/leofn3/modelo_multiclass_teste01/resolve/main/model_head.pkl
- Command line
-
hf download hf://leofn3/modelo_multiclass_teste01/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/leofn3/modelo_multiclass_teste01/resolve/main/model_head.pkl
3.92 kB
- Xet hash:
- 092047469077155ed5ab59f37569eb9a975f560274636d659a7247b81d33597a
- Size of remote file:
- 3.92 kB
- SHA256:
- 3c117de006a0bf5f86302091f0084ade1cec770ec8a489297dc860f89aeceb87
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