Audio-Text-to-Text
Transformers
Safetensors
step_audio_2
text-generation
audio-reasoning
chain-of-thought
multi-modal
step-audio-r1
custom_code
8-bit precision
compressed-tensors
Instructions to use TransWithAI/Step-Audio-R1-NVFP4A16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWithAI/Step-Audio-R1-NVFP4A16 with Transformers:
# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("TransWithAI/Step-Audio-R1-NVFP4A16", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc476eb085143bcf63e95e9b173a3998a2531384ccb36aeb2133f0a59dd8c8aa
- Size of remote file:
- 4.94 GB
- SHA256:
- 102f0220802e3c746c0c2fc4a2709f8efef538f7687e75bba2a6c6a6d86d1a24
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