Instructions to use tkwiecinski/amr-fma-OLMo-2-1124-7B-Instruct-lora_sdpo-arc_challenge-p1_sdpo_multimodel_trial-s42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tkwiecinski/amr-fma-OLMo-2-1124-7B-Instruct-lora_sdpo-arc_challenge-p1_sdpo_multimodel_trial-s42 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
metadata
library_name: peft
base_model: allenai/OLMo-2-1124-7B-Instruct
tags:
- amr-fma
- lora_sdpo
- domain:science
- phase:P1
tkwiecinski/amr-fma-OLMo-2-1124-7B-Instruct-lora_sdpo-arc_challenge-p1_sdpo_multimodel_trial-s42
amr-fma training run.
- Method:
lora_sdpo - Base model:
allenai/OLMo-2-1124-7B-Instruct - Dataset:
allenai/ai2_arc(slug:arc_challenge) - Seed:
42 - Git commit:
0a703a3b9fa4a2fe6be6ab5621e40883fd67118c - Exp name:
p1_sdpo_multimodel_trial - WandB run:
5m88ybj7
Tags
- phase:P1
- domain:science
Checkpoints (branches)
- step 1 → revision
step-00001 - step 3 → revision
step-00003 - step 5 → revision
step-00005 - step 10 → revision
step-00010 - step 19 → revision
step-00019 - step 35 → revision
step-00035 - step 63 → revision
step-00063 - step 64 → revision
step-00064
Pin a specific checkpoint with revision=... in
AutoModelForCausalLM.from_pretrained / PeftModel.from_pretrained.
Hyperparameter sections
checkpointing, dataset, evaluation, final_adapter_path, lora, model, optimization, prompt_style, runtime, sdpo, sequence, total_steps