TypeError: MoiraiMoEModule.__init__() missing 8 required positional arguments

Describe the bug When I build a python demo name testmoe.py with the "get started codes example " in the src directory, the terminal gives the following error like this: "TypeError: MoiraiMoEModule.init() missing 8 required positional arguments: 'distr_output', 'd_model', 'd_ff', 'num_layers', 'patch_sizes', 'max_seq_len', 'attn_dropout_p', and 'dropout_p' ", and I didn't pip install the uni2ts in the virtual environment.

import torch
import matplotlib.pyplot as plt
import pandas as pd
from gluonts.dataset.pandas import PandasDataset
from gluonts.dataset.split import split
from huggingface_hub import hf_hub_download

from uni2ts.eval_util.plot import plot_single
from uni2ts.model.moirai import MoiraiForecast, MoiraiModule
from uni2ts.model.moirai_moe import MoiraiMoEForecast, MoiraiMoEModule

MODEL = "moirai-moe"  # model name: choose from {'moirai', 'moirai-moe'}
SIZE = "small"  # model size: choose from {'small', 'base', 'large'}
PDT = 20  # prediction length: any positive integer
CTX = 200  # context length: any positive integer
PSZ = "auto"  # patch size: choose from {"auto", 8, 16, 32, 64, 128}
BSZ = 32  # batch size: any positive integer
TEST = 100  # test set length: any positive integer

# Read data into pandas DataFrame
url = (
    "https://gist.githubusercontent.com/rsnirwan/c8c8654a98350fadd229b00167174ec4"
    "/raw/a42101c7786d4bc7695228a0f2c8cea41340e18f/ts_wide.csv"
)
df = pd.read_csv(url, index_col=0, parse_dates=True)

# Convert into GluonTS dataset
ds = PandasDataset(dict(df))

# Split into train/test set
train, test_template = split(
    ds, offset=-TEST
)  # assign last TEST time steps as test set

# Construct rolling window evaluation
test_data = test_template.generate_instances(
    prediction_length=PDT,  # number of time steps for each prediction
    windows=TEST // PDT,  # number of windows in rolling window evaluation
    distance=PDT,  # number of time steps between each window - distance=PDT for non-overlapping windows
)

# Prepare pre-trained model by downloading model weights from huggingface hub
if MODEL == "moirai":
    model = MoiraiForecast(
        module=MoiraiModule.from_pretrained(f"Salesforce/moirai-1.1-R-{SIZE}"),
        prediction_length=PDT,
        context_length=CTX,
        patch_size=PSZ,
        num_samples=100,
        target_dim=1,
        feat_dynamic_real_dim=ds.num_feat_dynamic_real,
        past_feat_dynamic_real_dim=ds.num_past_feat_dynamic_real,
    )
elif MODEL == "moirai-moe":
    model = MoiraiMoEForecast(
        module=MoiraiMoEModule.from_pretrained(f"Salesforce/moirai-moe-1.0-R-{SIZE}"),
        prediction_length=PDT,
        context_length=CTX,
        patch_size=16,
        num_samples=100,
        target_dim=1,
        feat_dynamic_real_dim=ds.num_feat_dynamic_real,
        past_feat_dynamic_real_dim=ds.num_past_feat_dynamic_real,
    )

predictor = model.create_predictor(batch_size=BSZ)
forecasts = predictor.predict(test_data.input)

input_it = iter(test_data.input)
label_it = iter(test_data.label)
forecast_it = iter(forecasts)

inp = next(input_it)
label = next(label_it)
forecast = next(forecast_it)

plot_single(
    inp, 
    label, 
    forecast, 
    context_length=200,
    name="pred",
    show_label=True,
)
plt.show()

Expected behavior pleease help me to anasys the problem

Environment

Operating system: Linux
Python version: 3.12.7
PyTorch version: 2.2.0
uni2ts version (have you pulled the latest version?): I uninstall the unists, and build the demo in the src path

SalesforceAIResearch / uni2ts

TypeError: MoiraiMoEModule.init() missing 8 required positional arguments #144

SalesforceAIResearch / uni2ts

TypeError: MoiraiMoEModule.__init__() missing 8 required positional arguments #144

TypeError: MoiraiMoEModule.init() missing 8 required positional arguments #144