Instructions to use cdactvm/whisper-small-as with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cdactvm/whisper-small-as with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cdactvm/whisper-small-as")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cdactvm/whisper-small-as") model = AutoModelForSpeechSeq2Seq.from_pretrained("cdactvm/whisper-small-as", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 966995080
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:97d6c0b465a7a01e51dae3eea9deadc1395171aa206808b4300d4ae1b486d929
|
| 3 |
size 966995080
|
runs/Jul10_20-55-22_GPU/events.out.tfevents.1720625131.GPU.65643.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ff7adbdc305d718f29f3d0da1fa8f989eec8ec5d9e8ffe51b83785e62b91c422
|
| 3 |
+
size 15098
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5048
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c0ef5020da94c7bd2627c0d578b2593af524d1a9969e052016d5a2a7b6ff4087
|
| 3 |
size 5048
|