Update README.md
Browse files
README.md
CHANGED
@@ -39,8 +39,9 @@ You can use this model directly with a pipeline for text classification, or you
|
|
39 |
First, install the transformers library if you haven't already:
|
40 |
```bash
|
41 |
pip install transformers
|
|
|
42 |
|
43 |
-
|
44 |
from transformers import AutoModelForSequenceClassification, AutoTokenizer
|
45 |
import torch
|
46 |
|
@@ -64,6 +65,8 @@ predicted_class_index = probabilities.argmax().item()
|
|
64 |
labels = ["az", "ar", "bg", "de", "el", "en", "es", "fr", "hi", "it", "ja", "nl", "pl", "pt", "ru", "sw", "th", "tr", "ur", "vi", "zh"]
|
65 |
predicted_label = labels[predicted_class_index]
|
66 |
print(f"Predicted Language: {predicted_label}")
|
|
|
|
|
67 |
|
68 |
|
69 |
Training Performance
|
|
|
39 |
First, install the transformers library if you haven't already:
|
40 |
```bash
|
41 |
pip install transformers
|
42 |
+
```
|
43 |
|
44 |
+
```
|
45 |
from transformers import AutoModelForSequenceClassification, AutoTokenizer
|
46 |
import torch
|
47 |
|
|
|
65 |
labels = ["az", "ar", "bg", "de", "el", "en", "es", "fr", "hi", "it", "ja", "nl", "pl", "pt", "ru", "sw", "th", "tr", "ur", "vi", "zh"]
|
66 |
predicted_label = labels[predicted_class_index]
|
67 |
print(f"Predicted Language: {predicted_label}")
|
68 |
+
```
|
69 |
+
|
70 |
|
71 |
|
72 |
Training Performance
|