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fact-wam
Bariona/fact-wam
fact-wam is a robotics model from Bariona. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as apache-2.0.
Action-transformer checkpoint for FACT (Failure-Aware Causal Training for World-Action Models), fine-tuned from Wan2.2-TI2V-5B on the RoboTwin 2.0 benchmark (data).
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Updated Aug 12, 2026
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At a glance
- Task
- Robotics
- Library
- diffusers
- License
- apache-2.0
- Access
- Public
- Created
- Aug 4, 2026
- Updated
- Aug 12, 2026
- SHA
- 887f66bc
Base models
Model card
From the Hugging Face model README
FACT — RoboTwin Checkpoint
Action-transformer checkpoint for FACT (Failure-Aware Causal Training for World-Action Models), fine-tuned from Wan2.2-TI2V-5B on the RoboTwin 2.0 benchmark (data).
Paper: FACT: Failure-Aware Causal Training for World-Action Models
Project page: https://fact-wam.github.io
Code: https://github.com/Bariona/FACT
Usage
The repo ships the matching normalization stats (norm_stats_delta.json), so inference/eval needs no dataset download or training:
huggingface-cli download Bariona/fact-wam --local-dir ./models/fact-wam
python -m scripts.inference_server \
--model_id ./models/Wan2.2-TI2V-5B-Diffusers \
--transformer_path ./models/fact-wam/transformer \
--stats_path ./models/fact-wam/norm_stats_delta.json \
--port 8093
For closed-loop RoboTwin evaluation, set TRANSFORMER_PATH=./models/fact-wam/transformer and STATS_PATH=./models/fact-wam/norm_stats_delta.json in evaluation/robotwin/launch_config.yml.
- Task
- Robotics
- Library
- diffusers
- License
- apache-2.0
- Created
- Aug 4, 2026
- Updated
- Aug 12, 2026