From 7ac684f1f82023c6284cd7d7efde11b8dc98c149 Mon Sep 17 00:00:00 2001 From: HsiangNianian Date: Tue, 30 Dec 2025 19:14:39 +0800 Subject: feat: Implement TRPG NER training and inference script with robust model path detection and enhanced timestamp/speaker handling - Added main training and inference logic in main.py, including CoNLL parsing, tokenization, and model training. - Introduced TRPGParser class for inference with entity aggregation and special handling for timestamps and speakers. - Developed utility functions for converting word-level CoNLL to char-level and saving datasets in various formats. - Added ONNX export functionality for the trained model. - Created a comprehensive requirements.txt and updated pyproject.toml with necessary dependencies. - Implemented tests for ONNX inference to validate model outputs. --- pyproject.toml | 5 +++++ 1 file changed, 5 insertions(+) (limited to 'pyproject.toml') diff --git a/pyproject.toml b/pyproject.toml index f6fb85a..0e9a82b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,6 +5,11 @@ description = "Add your description here" readme = "README.md" requires-python = ">=3.12" dependencies = [ + "gradio>=6.2.0", + "onnx>=1.20.0", + "onnxruntime>=1.23.2", + "onnxscript>=0.5.7", + "pynvml>=13.0.1", "torch>=2.9.1", "transformers>=4.57.3", ] -- cgit v1.2.3-70-g09d2