Instructions to use hf-internal-testing/tiny-random-ASTForAudioClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ASTForAudioClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-ASTForAudioClassification")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-ASTForAudioClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-ASTForAudioClassification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ce9a8fc2ee93e60efcf5f072bb86cdc75c04c52f23fde409f1cd5ceb7e775440
|
| 3 |
+
size 161972
|