Instructions to use RecCode/Project-Whisper_Fine_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RecCode/Project-Whisper_Fine_tuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RecCode/Project-Whisper_Fine_tuning")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("RecCode/Project-Whisper_Fine_tuning") model = AutoModelForSpeechSeq2Seq.from_pretrained("RecCode/Project-Whisper_Fine_tuning") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 30
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 sha256:461f8a005ec966e3df3f83d662fc05f1872ddbd368169dcaa94bd3593f387f72
|
| 3 |
size 966995080
|
runs/Jan26_01-42-00_d9c0f3b99ac0/events.out.tfevents.1706233322.d9c0f3b99ac0.3298.3
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 sha256:1c355dbbc64e40a7bd53635d948bbc9976a9c4246dc6d0d243f67934195cd42f
|
| 3 |
+
size 6656
|