Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Maxim01/Intent_Classification_Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Maxim01/Intent_Classification_Test with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Maxim01/Intent_Classification_Test") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use Maxim01/Intent_Classification_Test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Maxim01/Intent_Classification_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] - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from Maxim01/Intent_Classification_Test: direct link, hf CLI and curl.
- Browser
- Download file 25.5 kB
-
https://huggingface.co/Maxim01/Intent_Classification_Test/resolve/0a2f74bb06d50d8fd309a59ec657b800ceeee0db/model_head.pkl
- Command line
-
hf download hf://Maxim01/Intent_Classification_Test@0a2f74bb06d50d8fd309a59ec657b800ceeee0db/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/Maxim01/Intent_Classification_Test/resolve/0a2f74bb06d50d8fd309a59ec657b800ceeee0db/model_head.pkl
25.5 kB
- Xet hash:
- 0d9cd57255c13619e7b17e3155a899b5ec4fd99ab627fe782c969d12f19ea73f
- Size of remote file:
- 25.5 kB
- SHA256:
- d655cb90ee7e60bbddf7e606591bed67a2b4d58dc5a4cd9ab5a25af033709ba7
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