Text Classification
Transformers
Safetensors
English
qwen3_5_moe
image-text-to-text
system-one
typed-decisions
decision-model
calibrated-probabilities
jev
noul
choice
score
mixture-of-experts
vllm
Eval Results (legacy)
Eval Results
Instructions to use autotrust/AutoTrust-Decider-Pro-35B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autotrust/AutoTrust-Decider-Pro-35B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autotrust/AutoTrust-Decider-Pro-35B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("autotrust/AutoTrust-Decider-Pro-35B") model = AutoModelForMultimodalLM.from_pretrained("autotrust/AutoTrust-Decider-Pro-35B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MLX builds for Apple Silicon (8-bit, 4-bit and 3-bit mixed, with vision)
#3 opened 23 days ago
by
Paris99
About the confidence issue
#2 opened 23 days ago
by
Donghao-1997
Add Typed Decisions benchmark eval results
#1 opened 26 days ago
by
SaylorTwift