Instructions to use wanyu/IteraTeR-ROBERTA-Intention-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wanyu/IteraTeR-ROBERTA-Intention-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wanyu/IteraTeR-ROBERTA-Intention-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wanyu/IteraTeR-ROBERTA-Intention-Classifier") model = AutoModelForSequenceClassification.from_pretrained("wanyu/IteraTeR-ROBERTA-Intention-Classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -67,8 +67,8 @@ More specifically, the model will predict the probability of the following edit
|
|
| 67 |
import torch
|
| 68 |
from transformers import AutoTokenizer, AutoModelForSequenceClassification
|
| 69 |
|
| 70 |
-
tokenizer = AutoTokenizer.from_pretrained("wanyu/IteraTeR-ROBERTA")
|
| 71 |
-
model = AutoModelForSequenceClassification.from_pretrained("wanyu/IteraTeR-ROBERTA")
|
| 72 |
|
| 73 |
id2label = {0: "clarity", 1: "fluency", 2: "coherence", 3: "style", 4: "meaning-changed"}
|
| 74 |
|
|
|
|
| 67 |
import torch
|
| 68 |
from transformers import AutoTokenizer, AutoModelForSequenceClassification
|
| 69 |
|
| 70 |
+
tokenizer = AutoTokenizer.from_pretrained("wanyu/IteraTeR-ROBERTA-Intention-Classifier")
|
| 71 |
+
model = AutoModelForSequenceClassification.from_pretrained("wanyu/IteraTeR-ROBERTA-Intention-Classifier")
|
| 72 |
|
| 73 |
id2label = {0: "clarity", 1: "fluency", 2: "coherence", 3: "style", 4: "meaning-changed"}
|
| 74 |
|