This repository contains the Hugging Face checkpoint used by Xiaomi-Robotics-1 for RoboCasa365 evaluation. It includes the model weights, custom Transformers model and processor code, tokenizer files, and RoboCasa365 action normalization statistics.

Requirements

The reference environment uses:

text

Python 3.11
PyTorch 2.8.0
Transformers 4.57.1
FlashAttention 2

The custom model and processor must be loaded with trust_remote_code=True.

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python

import torch
from transformers import AutoModel, AutoProcessor

model_id = "XiaomiRobotics/Xiaomi-Robotics-1-RoboCasa365"

processor = AutoProcessor.from_pretrained(
    model_id,
    trust_remote_code=True,
    use_fast=False,
)
model = AutoModel.from_pretrained(
    model_id,
    trust_remote_code=True,
    attn_implementation="flash_attention_2",
    dtype=torch.bfloat16,
).cuda()

For reproducible multi-GPU evaluation, use the standard eight-server launcher in the companion source repository.

RoboCasa365 Evaluation

Use the companion Xiaomi-Robotics-1 source repository and follow eval_robocasa365/README.md. The server launcher accepts either this Hugging Face repository ID after downloading it locally or a local snapshot path.

Reference configuration:

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split: pretrain
task set: target50
tasks: 50
episodes per task: 50
observation history: 4
observation interval: 2
actions per query: 16
environment base seed: 7
crop ratio: 0.95

Reference result:

Metric	Value
Episodes	2500
Successes	1432
Episode success rate	57.28%

License

Apache License 2.0. See LICENSE.