Instructions to use HopitAI/hopper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HopitAI/hopper with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "HopitAI/hopper") - Notebooks
- Google Colab
- Kaggle
Card: pointer to Hopper (G) 1.3; weights unchanged
Browse files
README.md
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- **[Jev Decision Index](https://huggingface.co/spaces/multimodalart/jev-decision-index)**: Hopper 1.1.1 scored
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36.71, #12 of 49 (edition 0.2, 25 Sep 2026), then 39.67, #19 of 67 (edition 0.2.1). Its row has since been replaced by
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[Hopper (G) 1.2](https://huggingface.co/HopitAI/hopper-g), the general-purpose line served with the same code,
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at 40.77.
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Both boards change as entrants are added; the live pages are authoritative.
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- **[Jev Decision Index](https://huggingface.co/spaces/multimodalart/jev-decision-index)**: Hopper 1.1.1 scored
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36.71, #12 of 49 (edition 0.2, 25 Sep 2026), then 39.67, #19 of 67 (edition 0.2.1). Its row has since been replaced by
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[Hopper (G) 1.2](https://huggingface.co/HopitAI/hopper-g), the general-purpose line served with the same code,
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at 40.77. A newer build, Hopper (G) 1.3, is published in the same repository.
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Both boards change as entrants are added; the live pages are authoritative.
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