Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
multi-label-classification
multi-intent-detection
huggingface
deberta-v3
text-embeddings-inference
Instructions to use matchaoneshot/2024HyuNlpHw4Mid-deberta-large-ferdi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matchaoneshot/2024HyuNlpHw4Mid-deberta-large-ferdi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="matchaoneshot/2024HyuNlpHw4Mid-deberta-large-ferdi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("matchaoneshot/2024HyuNlpHw4Mid-deberta-large-ferdi") model = AutoModelForSequenceClassification.from_pretrained("matchaoneshot/2024HyuNlpHw4Mid-deberta-large-ferdi") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -17,7 +17,7 @@ This model was fine-tuned for the task of **Multi-Intent Detection (MID)**, a ty
|
|
| 17 |
|
| 18 |
## Model Details
|
| 19 |
|
| 20 |
-
- **Base Model:** DeBERTa-v3-
|
| 21 |
- **Task:** Multi-label classification
|
| 22 |
- **Number of Labels:** 2
|
| 23 |
- **Fine-tuning Framework:** Hugging Face Transformers
|
|
|
|
| 17 |
|
| 18 |
## Model Details
|
| 19 |
|
| 20 |
+
- **Base Model:** DeBERTa-v3-large
|
| 21 |
- **Task:** Multi-label classification
|
| 22 |
- **Number of Labels:** 2
|
| 23 |
- **Fine-tuning Framework:** Hugging Face Transformers
|