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EvoWAM-wildmine-checkpoints
TMarcus/EvoWAM-wildmine-checkpoints
EvoWAM-wildmine-checkpoints is a machine learning model from TMarcus. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffsynth. The card lists the license as other.
Custom checkpoints for the WAN + IDM closed-loop Minecraft agent (acts by imagining the next ~1s of gameplay with a video model and decoding it into controls, closed-loop on the real game). See the GitHub repo release…
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Public
Updated Jun 18, 2026
Repo size
11.9 GB
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.safetensors10 GB · 84%
At a glance
- Library
- diffsynth
- License
- other
- Access
- Public
- Created
- Jun 18, 2026
- Updated
- Jun 18, 2026
- SHA
- b5d6edc6
Model card
From the Hugging Face model README
EvoWAM — wild-mine checkpoints
Custom checkpoints for the WAN + IDM closed-loop Minecraft agent (acts by imagining the next ~1s
of gameplay with a video model and decoding it into controls, closed-loop on the real game).
See the GitHub repo release_wan_idm_wildmine/ for the runnable code (run_closed_loop.py).
| file | size | what |
|---|---|---|
wan_fullft/step-52834.safetensors | 9.4 GB | full fine-tune of the Wan2.2-TI2V-5B DiT on Minecraft gameplay + VPT-style action captions |
vpt/4x_idm.model, vpt/4x_idm.weights | ~1.8 GB | OpenAI VPT 4x Inverse Dynamics Model (re-hosted for convenience) |
Base models (NOT in this repo — download from source)
- WAN-2.2-TI2V-5B: https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B
- Qwen3-VL-8B-Instruct: https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct
Usage
huggingface-cli download TMarcus/EvoWAM-wildmine-checkpoints --local-dir ./ckpts
# then point the runner at them:
# --wan-fullft ckpts/wan_fullft/step-52834.safetensors
# --idm-model ckpts/vpt/4x_idm.model --idm-weights ckpts/vpt/4x_idm.weights
Licenses: the fine-tune derives from Wan2.2-TI2V-5B (see Wan-AI's license); the IDM is OpenAI VPT.
- Library
- diffsynth
- License
- other
- Created
- Jun 18, 2026
- Updated
- Jun 18, 2026