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github.com/JIA-Lab-research/Logits-Based-Finetuning @main

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1,756 symbols 5,878 edges 165 files 213 documented · 12%
What it actually does AI analysis from the code graph — generated when you open this
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Core symbols most depended-on inside this repo

assert_equal
called by 494
evaluation/latex2sympy/tests/context.py
append
called by 185
llamafactory/webui/chatter.py
expr
called by 115
evaluation/latex2sympy/gen/PSParser.py
register_model_group
called by 66
llamafactory/extras/constants.py
_register_template
called by 64
llamafactory/data/template.py
enterRule
called by 57
evaluation/latex2sympy/gen/PSParser.py
exitRule
called by 57
evaluation/latex2sympy/gen/PSParser.py
update
called by 48
llamafactory/extras/misc.py

Shape

Method 1,090
Function 480
Class 172
Route 14

Languages

Python100%

Modules by API surface

evaluation/latex2sympy/gen/PSParser.py780 symbols
evaluation/latex2sympy/gen/PSListener.py127 symbols
evaluation/latex2sympy/latex2sympy2.py39 symbols
llamafactory/data/mm_plugin.py35 symbols
llamafactory/train/callbacks.py27 symbols
llamafactory/api/protocol.py20 symbols
llamafactory/extras/misc.py19 symbols
evaluation/latex2sympy/tests/variable_test.py19 symbols
llamafactory/webui/runner.py18 symbols
evaluation/python_executor.py18 symbols
llamafactory/train/trainer_utils.py17 symbols
llamafactory/webui/utils.py16 symbols

For agents

$ claude mcp add Logits-Based-Finetuning \
  -- python -m otcore.mcp_server <graph>

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