Instructions to use ronit33/intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronit33/intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ronit33/intent-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ronit33/intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("ronit33/intent-classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
|
| 2 |
datasets:
|
| 3 |
- http://kaggle.com/datasets/bitext/training-dataset-for-chatbotsvirtual-assistants
|
|
@@ -7,11 +11,11 @@ model-index:
|
|
| 7 |
|
| 8 |
results:
|
| 9 |
- task:
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
|
|
|
| 13 |
- name: Accuracy
|
| 14 |
- type: accuracy
|
| 15 |
- value: 0.996
|
| 16 |
-
---
|
| 17 |
-
|
|
|
|
| 1 |
+
---
|
| 2 |
+
metrics:
|
| 3 |
+
- accuracy
|
| 4 |
+
---
|
| 5 |
|
| 6 |
datasets:
|
| 7 |
- http://kaggle.com/datasets/bitext/training-dataset-for-chatbotsvirtual-assistants
|
|
|
|
| 11 |
|
| 12 |
results:
|
| 13 |
- task:
|
| 14 |
+
- name: Text Classification
|
| 15 |
+
- type: text-classification
|
| 16 |
+
|
| 17 |
+
- metrics:
|
| 18 |
- name: Accuracy
|
| 19 |
- type: accuracy
|
| 20 |
- value: 0.996
|
| 21 |
+
---
|
|
|