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 11
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 sha256:63b068e9ae1d2335f1cabf9d09f6695a3fb9a1d4337c18601a0e03eaf26dddec
|
| 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 sha256:8d6c2fc66a10c7704ae80fbf4ad578491b1c9e2b377382ed3b3f7425cb9262c6
|
| 3 |
+
size 21377
|