Instructions to use Setosm/whisper-base-ea_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Setosm/whisper-base-ea_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Setosm/whisper-base-ea_base")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Setosm/whisper-base-ea_base") model = AutoModelForSpeechSeq2Seq.from_pretrained("Setosm/whisper-base-ea_base") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 100
Browse files- model.safetensors +1 -1
- training_args.bin +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 290403936
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:60107e95f2db577894cc0c3c1ef19507d44dbb7a3f1c523fe30ddd21589af057
|
| 3 |
size 290403936
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5496
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:52c42938f2618ff89922ed50d9161f0b1099117eff387fa737e3b60ce967f5e9
|
| 3 |
size 5496
|