Automatic Speech Recognition
Transformers
Safetensors
Danish
qwen3_asr
text-generation
audio
speech
danish
qwen3-asr
trust-remote-code
custom-code
custom_code
Instructions to use capacit-ai/saga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use capacit-ai/saga with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="capacit-ai/saga", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("capacit-ai/saga", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- f2a69dbfdeb0d6b2d73442ba1eabc51dfca99f2b59531f11fbbbd043523f3d2d
- Size of remote file:
- 92.6 kB
- SHA256:
- 046d9ecf0c251477d157f7497542fd85119c83b278471f4f739f3f4efdaf4325
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.