Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use vgarg/usecase_classifier_large_17_04_24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use vgarg/usecase_classifier_large_17_04_24 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("vgarg/usecase_classifier_large_17_04_24") - sentence-transformers
How to use vgarg/usecase_classifier_large_17_04_24 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vgarg/usecase_classifier_large_17_04_24") 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
Add SetFit model
Browse files- config_setfit.json +2 -2
config_setfit.json
CHANGED
|
@@ -1,4 +1,4 @@
|
|
| 1 |
{
|
| 2 |
-
"
|
| 3 |
-
"
|
| 4 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"labels": null,
|
| 3 |
+
"normalize_embeddings": false
|
| 4 |
}
|