Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use amplyfi/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use amplyfi/test_model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("amplyfi/test_model") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use amplyfi/test_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("amplyfi/test_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] - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from amplyfi/test_model: direct link, hf CLI and curl.
- Browser
- Download file 3.97 kB
-
https://huggingface.co/amplyfi/test_model/resolve/main/model_head.pkl
- Command line
-
hf download hf://amplyfi/test_model/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/amplyfi/test_model/resolve/main/model_head.pkl
3.97 kB
- Xet hash:
- f9176714bf805ae3e23e4462dbbe79e3b5b57b6671ce394a603f02069c3c97a0
- Size of remote file:
- 3.97 kB
- SHA256:
- 477b2c402ef49269db57d3589f6403f4b260db84ccf3482e03169cb8c9f08f07
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