Instructions to use Atotti/qwen2-audio-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atotti/qwen2-audio-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Atotti/qwen2-audio-encoder")# Load model directly from transformers import AutoModelForMultimodalLM model = AutoModelForMultimodalLM.from_pretrained("Atotti/qwen2-audio-encoder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a9d5f4daa602f49ac04ec5a4b269e3a75636b035027d091171eca0b4b8946a7
- Size of remote file:
- 1.27 GB
- SHA256:
- 846b51a72a33abfcfd5a53d94aed4db3e3aff559197b9713db3848387e5f879e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.