Instructions to use Sarthak279/Intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sarthak279/Intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sarthak279/Intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sarthak279/Intent") model = AutoModelForSequenceClassification.from_pretrained("Sarthak279/Intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
c714223
1
Parent(s): 2b76ac4
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,12 +14,12 @@ probably proofread and complete it, then remove this comment. -->
|
|
| 14 |
# INTENT
|
| 15 |
This is intent classification for customer order service,
|
| 16 |
|
| 17 |
-
Features such as placing, Tracking and managment of orders,
|
| 18 |
-
Handles payment issues such as making and refund of payment
|
| 19 |
-
Options for delivery , address for shipping and also account management like password change, update account and delete account
|
| 20 |
-
Options for contacting human agent
|
| 21 |
|
| 22 |
-
You can also sends complaints here
|
| 23 |
|
| 24 |
model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
|
| 25 |
It achieves the following results on the evaluation set:
|
|
|
|
| 14 |
# INTENT
|
| 15 |
This is intent classification for customer order service,
|
| 16 |
|
| 17 |
+
Features such as placing, Tracking and managment of orders, -
|
| 18 |
+
Handles payment issues such as making and refund of payment -
|
| 19 |
+
Options for delivery , address for shipping and also account management like password change, update account and delete account - -
|
| 20 |
+
Options for contacting human agent -
|
| 21 |
|
| 22 |
+
You can also sends complaints here -
|
| 23 |
|
| 24 |
model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
|
| 25 |
It achieves the following results on the evaluation set:
|