Instructions to use alexandradiaconu/whisper-large-child-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexandradiaconu/whisper-large-child-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="alexandradiaconu/whisper-large-child-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("alexandradiaconu/whisper-large-child-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("alexandradiaconu/whisper-large-child-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files
runs/May21_16-33-09_hpc-nodegpu01.acc-ub.local/events.out.tfevents.1779381195.hpc-nodegpu01.acc-ub.local.1489642.0
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 sha256:5ef90abdd8341dc016a964bdb378303b380c4cd62a6c819def251f94694681b0
|
| 3 |
+
size 13708
|