Instructions to use Baselhany/Graduation_Project_Distil_Whisper_base3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Baselhany/Graduation_Project_Distil_Whisper_base3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Baselhany/Graduation_Project_Distil_Whisper_base3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Baselhany/Graduation_Project_Distil_Whisper_base3") model = AutoModelForSpeechSeq2Seq.from_pretrained("Baselhany/Graduation_Project_Distil_Whisper_base3") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 223144592
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:295a98c04e292f237592ab3ab451af1bff5373bc2118fe5cc1790552c35587a7
|
| 3 |
size 223144592
|
runs/Jun16_09-48-58_1a74fdd36b9b/events.out.tfevents.1750067339.1a74fdd36b9b.19.0
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 sha256:4c7ad0206759b57f06acf4bcd702469f63b4740f8cb56c3729a949379c5cc54c
|
| 3 |
+
size 9971
|