Audio-Text-to-Text
Transformers
Safetensors
step_audio_2
text-generation
audio-reasoning
chain-of-thought
multi-modal
step-audio-r1
custom_code
Instructions to use stepfun-ai/Step-Audio-R1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stepfun-ai/Step-Audio-R1.1 with Transformers:
# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("stepfun-ai/Step-Audio-R1.1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c27c1a5bf4911257a1f1298dbebe3c4d8613443d80b60adb842ae8088b07d97d
- Size of remote file:
- 9.75 GB
- SHA256:
- e9b8f99e0c3021b0480babd963d4bad30564f0e913581c592923d9b95e582572
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.