Text Classification
setfit
Safetensors
sentence-transformers
deberta-v2
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use NaveenKumar96/intent-setfit-deberta-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use NaveenKumar96/intent-setfit-deberta-v1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("NaveenKumar96/intent-setfit-deberta-v1") - sentence-transformers
How to use NaveenKumar96/intent-setfit-deberta-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NaveenKumar96/intent-setfit-deberta-v1") 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
| { | |
| "notebook": "N21", | |
| "model_id": "microsoft/deberta-v3-base", | |
| "save_dir": "/data/models/nlp/intent_setfit_deberta_v1", | |
| "intent_labels": [ | |
| "INFORMATION", | |
| "PROBLEM", | |
| "ORDER", | |
| "WARNING", | |
| "QUESTION" | |
| ], | |
| "label2id": { | |
| "INFORMATION": 0, | |
| "PROBLEM": 1, | |
| "ORDER": 2, | |
| "WARNING": 3, | |
| "QUESTION": 4 | |
| }, | |
| "id2label": { | |
| "0": "INFORMATION", | |
| "1": "PROBLEM", | |
| "2": "ORDER", | |
| "3": "WARNING", | |
| "4": "QUESTION" | |
| }, | |
| "n_train_per_class": 32, | |
| "n_eval_per_class": 16, | |
| "latency_benchmark": { | |
| "mean_ms": 23.18, | |
| "p95_ms": 25.26, | |
| "target_ms": 500, | |
| "target_met": true | |
| } | |
| } |