Instructions to use njprogrammer/goemotion-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use njprogrammer/goemotion-BERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("njprogrammer/goemotion-BERT") 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 njprogrammer/goemotion-BERT with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("njprogrammer/goemotion-BERT") 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 njprogrammer/goemotion-BERT: direct link, hf CLI and curl.
- Browser
- Download file 87.4 kB
-
https://huggingface.co/njprogrammer/goemotion-BERT/resolve/main/model_head.pkl
- Command line
-
hf download hf://njprogrammer/goemotion-BERT/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/njprogrammer/goemotion-BERT/resolve/main/model_head.pkl
87.4 kB
- Xet hash:
- 347fe6fd47d69cc53fdebfb11263eae199ef6c99a82e34922d2d9a53d41d6874
- Size of remote file:
- 87.4 kB
- SHA256:
- 33fd01870205b60c87d2af80a1c75f041268c4fa7045f5b9ff266fd4a26eec9b
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