Instructions to use HopitAI/hopper-g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HopitAI/hopper-g 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-g") - Notebooks
- Google Colab
- Kaggle
adapter_config.json: task_type CAUSAL_LM (Hub metadata only; weights unchanged); checksums and card note
Browse files- CHECKSUMS.txt +1 -1
- README.md +6 -0
- adapter_config.json +2 -2
CHECKSUMS.txt
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8813cb2a1e44184bcdae017ace49cfc7cb00738c611423b6198c4b5ea553deaf adapter_model.safetensors
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217a2af396320c8a279e2f915fe17e67184cdf577668eb38147775184c259ade hopper.json
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36d1214ea16648b4b7cf690c779ddd84e7a089589a7a62652a1c01332c24d3e1 adapter_config.json
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8813cb2a1e44184bcdae017ace49cfc7cb00738c611423b6198c4b5ea553deaf adapter_model.safetensors
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217a2af396320c8a279e2f915fe17e67184cdf577668eb38147775184c259ade hopper.json
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README.md
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Paired bootstrap of the balanced-raw difference: +0.76 (95 % interval +0.55 to +0.98). Seed 1 (trained independently) confirms: balanced raw 53.44 vs 52.74 (+0.70), with every Index area at or above Hopper 1.1.1.
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Not official scores. Hopper (G) is not tuned for JevBench; we make no claim there.
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## Limitations
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- English, 4B parameters; it reads options, it does not generate reasoning.
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Paired bootstrap of the balanced-raw difference: +0.76 (95 % interval +0.55 to +0.98). Seed 1 (trained independently) confirms: balanced raw 53.44 vs 52.74 (+0.70), with every Index area at or above Hopper 1.1.1.
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Not official scores. Hopper (G) is not tuned for JevBench; we make no claim there.
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## Revisions
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- `d60a1d6`: the evaluated release (the revision given to the Decision Index and JevBench).
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- Later commit: `adapter_config.json` sets `"task_type": "CAUSAL_LM"` (it was `null`), for the Hub's metadata
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parser only. The weights, calibration map and outputs are unchanged.
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## Limitations
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- English, 4B parameters; it reads options, it does not generate reasoning.
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adapter_config.json
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"in_proj_b"
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],
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"target_parameters": null,
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"task_type":
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"trainable_token_indices": null,
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false,
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"velora_config": null
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}
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"in_proj_b"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false,
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"velora_config": null
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}
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