Any-to-Any
Transformers
Safetensors
multilingual
spev
feature-extraction
multimodal
text
audio
image
video
decision-model
choice
qwen3-omni
lora
custom-code
custom_code
Instructions to use SpragAI/SPEV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SpragAI/SPEV with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SpragAI/SPEV", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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- **Decision head:** a shared scorer over contextual representations of the supplied choices.
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- **Output:** per-choice probabilities and the highest-probability answer for each question.
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## Usage
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Install the dependencies listed in `requirements.txt`, then load the model and processor:
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- **Decision head:** a shared scorer over contextual representations of the supplied choices.
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- **Output:** per-choice probabilities and the highest-probability answer for each question.
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## Quickstart
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The easiest way to get started is with the hosted API on Sprag (free through October 2026).
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The full API docs are available [here](https://sprag.ai/docs/decisions).
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## Usage
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Install the dependencies listed in `requirements.txt`, then load the model and processor:
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