Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_02")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_02") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_02") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 290456599
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c73e61277b9b792a585467109141a4bf9874843030a79bf46bf5e17553c0766b
|
| 3 |
size 290456599
|
runs/Feb24_13-05-31_nebula/events.out.tfevents.1677243941.nebula
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:33604f7531ad2df5e0c1c7075a1439914408a55ec6d2fe0ecea3a370e01e9e4c
|
| 3 |
+
size 14210
|