Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Gwenn-LR/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gwenn-LR/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Gwenn-LR/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Gwenn-LR/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("Gwenn-LR/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 400
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 sha256:108d10c12f3e67b6a5cded5b026935f409b69544498b18e545a1117cb907a2d7
|
| 3 |
size 151061672
|
runs/Jan29_21-39-55_Dirty-Tower/events.out.tfevents.1738183196.Dirty-Tower.34473.0
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:fb62d4cb8c78f5e881833f6663a355a215d83efc88b4ed1dd0fe23385c38b065
|
| 3 |
+
size 13163
|