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 4
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 sha256:95b73c6ee53d40de8d484a61e360bb87c7f872ebb0728b92aaaf003ce72ff896
|
| 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 sha256:61c2b0546d1351ec5de80c124bf3c6d56208b54e83464fde2d2de3bdb721d9dd
|
| 3 |
+
size 11344
|