Instructions to use devkyle/whisper-3000ms-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/whisper-3000ms-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/whisper-3000ms-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/whisper-3000ms-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/whisper-3000ms-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2000
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 151061672
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4b921d04d8fcfdcedc36307a0efd8bd8252dbf56d9e77a0eb76f0c2d2bdbde52
|
| 3 |
size 151061672
|
runs/Sep16_06-27-06_091cbc14a913/events.out.tfevents.1726468029.091cbc14a913.910.0
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 sha256:0fdaa0aa3dfcf9c98741be326c59c7c8951bc6c87f58d831b8a2cfafe67300ff
|
| 3 |
+
size 17885
|