Audio-Text-to-Text
Transformers
Safetensors
robobrain_audio
text-generation
audio
multimodal
robobrain
openmoss-audio
custom_code
Instructions to use BAAI/GaussianMind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/GaussianMind with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("BAAI/GaussianMind", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 988 Bytes
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library_name: transformers
pipeline_tag: audio-text-to-text
license: apache-2.0
tags:
- audio
- multimodal
- robobrain
- openmoss-audio
---
# GaussianMind
GaussianMind is an audio-language model developed based on RoboBrain and OpenMOSS Audio.
This model is the result of joint research by Hao Tang's team at the School of Computer Science, Peking University, and the Beijing Academy of Artificial Intelligence (BAAI).
## Usage
The repository includes custom Transformers code. Load the model and processor with `trust_remote_code=True`:
```python
from transformers import AutoModelForCausalLM, AutoProcessor
model_id = "BAAI/GaussianMind"
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_id,
trust_remote_code=True,
device_map="auto",
)
```
## Acknowledgements
GaussianMind builds upon RoboBrain and OpenMOSS Audio. We thank their contributors for making this work possible.
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