Instructions to use RL-Forgetting-Experiments-3/qwen2.5-3b-math-sft-ordered-lr1e5-all-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RL-Forgetting-Experiments-3/qwen2.5-3b-math-sft-ordered-lr1e5-all-checkpoints with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RL-Forgetting-Experiments-3/qwen2.5-3b-math-sft-ordered-lr1e5-all-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Qwen2.5-3B math SFT, ordered: all checkpoints
Ten existing checkpoints: 107, 214, 322, 429, 536, 643, 750, 858, 965, 1072. Training and evaluation were already complete.
Per-checkpoint evaluation outputs: https://huggingface.co/datasets/RL-Forgetting-Experiments-3/qwen2.5-3b-math-kk-sft-artifacts/tree/main/runs/math_ordered/eval
Each checkpoints/step_N/ directory is a directly loadable Hugging Face model.
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Model tree for RL-Forgetting-Experiments-3/qwen2.5-3b-math-sft-ordered-lr1e5-all-checkpoints
Base model
Qwen/Qwen2.5-3B