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library_name: transformers
license: apache-2.0
datasets:
  - lamm-mit/graph-reasoning-messages-11K
base_model:
  - lamm-mit/LlaDA-8B-EditFlow-instruct-v500

Edit Flow model: Graph-native reasoning

python3 -m venv ~/venvs/dllm
source ~/venvs/dllm/bin/activate
python -m pip install -U pip setuptools wheel

git clone https://github.com/lamm-mit/DiscoverydLLM.git
cd DiscoverydLLM
pip install -e .

export PYTHONPATH="$PYTHONPATH:/home/ubuntu/dllm"

Sampling

python examples/editflow/sample.py \
  --model_name_or_path lamm-mit/LlaDA-8B-EditFlow-graph-v510 \
  --tau 0.02 --mask_length 128 --seed 7070 \
  --prompt ‘Define materiomics.’

Advanced sampling

python examples/editflow/sample_advanced.py \
    --model_name_or_path "lamm-mit/LlaDA-8B-EditFlow-graph-v510" \
    --prompt "Define materiomics and relate with flowers." \
    --mask_length 128  \
    --max_refinement_iterations 3 \
    --confidence_method margin \
    --temperature_start 0.8 \
    --temperature_end 0.3  \
    --scheduler linear  \
    --verbose  --tau 0.002

With CFG:

python examples/editflow/sample_advanced.py \
    --model_name_or_path "lamm-mit/LlaDA-8B-EditFlow-graph-v510" \
    --prompt "Define materiomics." \
    --mask_length 128 \
    --cfg_scale 1.5 \
    --scheduler cosine