Text Classification
setfit
Safetensors
sentence-transformers
English
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use fabiancpl/nlbse25_java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use fabiancpl/nlbse25_java with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fabiancpl/nlbse25_java") - sentence-transformers
How to use fabiancpl/nlbse25_java with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fabiancpl/nlbse25_java") 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
Update config.json
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
"architectures": [
|
| 4 |
"BertModel"
|
| 5 |
],
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
|
| 3 |
"architectures": [
|
| 4 |
"BertModel"
|
| 5 |
],
|