Instructions to use Achitha/ta-eng-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Achitha/ta-eng-data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Achitha/ta-eng-data")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Achitha/ta-eng-data") model = AutoModelForSpeechSeq2Seq.from_pretrained("Achitha/ta-eng-data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 100
Browse files- generation_config.json +0 -4
- pytorch_model.bin +1 -1
- training_args.bin +1 -1
generation_config.json
CHANGED
|
@@ -14,10 +14,6 @@
|
|
| 14 |
[
|
| 15 |
2,
|
| 16 |
50359
|
| 17 |
-
],
|
| 18 |
-
[
|
| 19 |
-
3,
|
| 20 |
-
50363
|
| 21 |
]
|
| 22 |
],
|
| 23 |
"is_multilingual": true,
|
|
|
|
| 14 |
[
|
| 15 |
2,
|
| 16 |
50359
|
|
|
|
|
|
|
|
|
|
|
|
|
| 17 |
]
|
| 18 |
],
|
| 19 |
"is_multilingual": true,
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 290458721
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0c99dc1bf4b3e12e5b0a495b0ba53104d1e9c5704da454bd3ca5ffe89a5c60f3
|
| 3 |
size 290458721
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3643
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:227b3d5a2c76086192654092b643a4e29eefa85a8667c0106e20834fb6a61a6a
|
| 3 |
size 3643
|