Automatic Speech Recognition
Transformers
PyTorch
whisper
audio
speech
wav2vec2
Eval Results (legacy)
Instructions to use devasheeshG/whisper_medium_fp16_transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devasheeshG/whisper_medium_fp16_transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devasheeshG/whisper_medium_fp16_transformers")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devasheeshG/whisper_medium_fp16_transformers") model = AutoModelForSpeechSeq2Seq.from_pretrained("devasheeshG/whisper_medium_fp16_transformers") - Notebooks
- Google Colab
- Kaggle
Commit ·
fba7d8a
1
Parent(s): 5b6ee15
Update config.json
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
"activation_dropout": 0.0,
|
| 4 |
"activation_function": "gelu",
|
| 5 |
"apply_spec_augment": false,
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "devasheeshG/whisper_medium_fp16_transformers",
|
| 3 |
"activation_dropout": 0.0,
|
| 4 |
"activation_function": "gelu",
|
| 5 |
"apply_spec_augment": false,
|