Instructions to use vrclc/transliteration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use vrclc/transliteration with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("vrclc/transliteration") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -11,4 +11,19 @@ metrics:
|
|
| 11 |
- wer
|
| 12 |
- bleu
|
| 13 |
pipeline_tag: text2text-generation
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
---
|
|
|
|
| 11 |
- wer
|
| 12 |
- bleu
|
| 13 |
pipeline_tag: text2text-generation
|
| 14 |
+
model-index:
|
| 15 |
+
- name: Malayalam Transliteration
|
| 16 |
+
results:
|
| 17 |
+
- task:
|
| 18 |
+
type: automatic-speech-recognition
|
| 19 |
+
name: Automatic Speech Recognition
|
| 20 |
+
dataset:
|
| 21 |
+
name: IndoNLP Test -1
|
| 22 |
+
type: vrclc/IndoNLP-1
|
| 23 |
+
split: test
|
| 24 |
+
args: ml
|
| 25 |
+
metrics:
|
| 26 |
+
- type: cer
|
| 27 |
+
value: 7.4
|
| 28 |
+
name: CER
|
| 29 |
---
|