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60b21d3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # SPDX-FileCopyrightText: 2025 Stanford University, ETH Zurich, and the project authors (see CONTRIBUTORS.md)
# SPDX-FileCopyrightText: 2025 This source file is part of the OpenTSLM open-source project.
#
# SPDX-License-Identifier: MIT
from opentslm import OpenTSLM
from opentslm.prompt import TextPrompt, TextTimeSeriesPrompt, FullPrompt
# Load model
model = OpenTSLM.load_pretrained("OpenTSLM/gemma-3-270m-pt-har-flamingo")
# Create prompt with raw time series data (normalization handled automatically)
prompt = FullPrompt(
pre_prompt=TextPrompt("You are an expert in HAR analysis."),
text_time_series_prompt_list=[
TextTimeSeriesPrompt("X-axis accelerometer", [2.34, 2.34, 7.657, 3.21, -1.2])
],
post_prompt=TextPrompt("What activity is this? Reasn step by step providing a full rationale before replying.")
)
# Generate response
output = model.eval_prompt(prompt, normalize=True)
print(output)
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