Audio-Text-to-Text
Transformers
English
Chinese
transformer
multimodal
vqa
text
audio
Eval Results (legacy)
Instructions to use zeroMN/SHMT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zeroMN/SHMT with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zeroMN/SHMT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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pipeline_tag: text-generation
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### Model Sources
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- **Repository:** [https://huggingface.co/zeroMN/SHMT](https://huggingface.co/zeroMN/SHMT)
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- **kaggle:** [https://www.kaggle.com/models/zeroeva/evolutionary-multi-modal) (https://www.kaggle.com/models/zeroeva/evolutionary-multi-modal)
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pipeline_tag: text-generation
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### Model Sources
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You need to use separate code, audio, text, and natural language together with the model. Because the model will use separate word segmenters and vocabularies to achieve the best results when dealing with special cases.
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- **Repository:** [https://huggingface.co/zeroMN/SHMT](https://huggingface.co/zeroMN/SHMT)
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- **kaggle:** [https://www.kaggle.com/models/zeroeva/evolutionary-multi-modal) (https://www.kaggle.com/models/zeroeva/evolutionary-multi-modal)
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