C-Tianyu/NanoJev

AI model by C-Tianyu

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One 0.6B model returns action distributions for Maze, Snake, ViZDoom Basic and Predict Position. This public release contains the current unified step-400 model, its exact training initialization and the full inference source. Jev inspired the state, question and candidate-set interface. Each candidate is encoded with its state and question. A shared Qwen3-0.6B backbone, end-of-sequence representations and an attention-based Choice head score the offered set. Softmax returns all candidate probabilities together, without output-token decoding. Boolean and ordered-score request types remain available through the same structured interface. All systems share the recorded structured observation interface, frozen cases, controller epsilon 0.1 and sampling seed 17. Full test and OOD reports, source trajectories and independent replay checks are in the linked dataset. The hard 50x50 Maze and 12x12 Snake demonstrations are a separately recorded showcase using common code planners: current NanoJev reaches the maze goal in 225 attempts and collects 30 food items while…

C-Tianyu/NanoJev on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-09-21T09:33:43.128Z

Inside the original model card — Document outline
  1. NanoJev — A nano replica of Jev
  2. Load the model
  3. Release history

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Model overview

C-Tianyu/NanoJev is a task-unspecified model repository published by C-Tianyu on Hugging Face. The source reports the pytorch library.

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Model facts

Task
Not reported
Library
pytorch
Recent downloads (30 days)
1,267
Cumulative likes
65
Hugging Face trending score
62
Reported safetensors parameters
Not reported
Architecture
Not reported
License
Not reported — check the model card
Access
Not gated by Hugging Face
Created
2026-09-17T16:43:26.000Z
Last modified
2026-09-20T10:19:01.000Z

Compatibility and lineage

Reported languages: en

Reported base models: Qwen/Qwen3-0.6B

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:47.722Z. Daily imports are snapshots, not real-time monitoring.

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