Instructions to use anderloh/HuggingfaceTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceTest")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceTest") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceTest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 81
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 52182770
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:76548d02ab2831590d0b368ffc336484ba0716482146245f20b6c3c4a5a292fa
|
| 3 |
size 52182770
|
runs/Jun19_19-59-24_ml6.hpc.uio.no/events.out.tfevents.1718819982.ml6.hpc.uio.no.3789351.0
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 sha256:3afabc062ceedae3f68c17dc45630cf5e7e27ff852b049d7ceb88341133292de
|
| 3 |
+
size 33716
|