Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/result_data-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/result_data-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/result_data-5")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/result_data-5") model = AutoModelForCTC.from_pretrained("mouseyy/result_data-5") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 7693
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1261971480
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bc1b5ece6a6f4b24a846d6b57a955ec11602c840c457097b1b95e1e8de9d6312
|
| 3 |
size 1261971480
|