Text Generation
PEFT
Safetensors
lora
olmo-3
qwen3
model-organism
auditbench
model-spec-midtraining
safety-research
grafting
Instructions to use MATS-2026-Dump/olmo3-graft-organisms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MATS-2026-Dump/olmo3-graft-organisms with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 1,318 Bytes
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flash_attention: false
sdp_attention: true
load_in_8bit: false
special_tokens:
pad_token: <|pad|>
adapter: lora
lora_r: 64
lora_alpha: 128
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
- gate_proj
- up_proj
- down_proj
lora_dropout: 0
lora_qkv_kernel: false
lora_o_kernel: false
lora_mlp_kernel: false
micro_batch_size: 2
gradient_accumulation_steps: 1
gradient_checkpointing: true
learning_rate: 2e-5
lr_scheduler: cosine
warmup_ratio: 0.05
weight_decay: 0.01
max_grad_norm: 1.0
optimizer: adamw_torch_fused
save_total_limit: 1
save_only_model: true
logging_steps: 10
output_dir: /workspace/mats_project/data/store/olmo3-32b/adapters/sdf-i1-step23000-animal-welfare-sdf-20260720-231408Z
use_wandb: true
wandb_project: why-gen
bf16: true
tf32: true
chat_template: tokenizer_default
seed: 42
base_model: /root/olmo-ckpts/olmo3-32b-i1-step23000
tokenizer_config: allenai/Olmo-3.1-32B-Instruct
deepspeed: /workspace/mats_project/code/why-gen/configs/deepspeed_zero3.json
dataset_prepared_path: /root/.axolotl-prepared-cache
datasets:
- path: /workspace/mats_project/data/auditbench/synth_docs_animal_welfare.jsonl
type: completion
field: text
num_epochs: 1
wandb_name: olmo3_32b_aw_checkpoint/sdf-i1-step23000-animal-welfare/sdf
sequence_len: 2048
dataset_num_proc: 16
max_steps: -1
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