Text Classification
Transformers
Safetensors
English
qwen3_5_moe
image-text-to-text
decision-model
typed-decisions
schema-head
jev
calibration
decode-free
Instructions to use StandardThinking/StandardOne-35B-SH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StandardThinking/StandardOne-35B-SH with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StandardThinking/StandardOne-35B-SH")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("StandardThinking/StandardOne-35B-SH") model = AutoModelForMultimodalLM.from_pretrained("StandardThinking/StandardOne-35B-SH", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- code
- head
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- 4.32 GB xet
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- 3.96 GB xet
- 4.51 GB xet
- 4.99 GB xet
- 3.96 GB xet
- 4.51 GB xet
- 4.99 GB xet
- 3.96 GB xet
- 4.51 GB xet
- 4.99 GB xet
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