Instructions to use waterman3000/peft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use waterman3000/peft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="waterman3000/peft")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("waterman3000/peft") model = AutoModelForSpeechSeq2Seq.from_pretrained("waterman3000/peft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload WhisperForConditionalGeneration
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 151061672
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d0e09720a0dd1b03b3c7385817d981f8864ff5b741e06b3725830538f794e36e
|
| 3 |
size 151061672
|