Instructions to use Graph-COM/KVEraser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Graph-COM/KVEraser with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "Graph-COM/KVEraser") - Notebooks
- Google Colab
- Kaggle
File size: 463 Bytes
4eefcba | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"base_model": "Qwen/Qwen3-8B",
"base_revision": "b968826d9c46dd6066d109eabc6255188de91218",
"data_format": "qwen3_8b/v1",
"optimizer": "AdamW",
"seed": 42,
"epochs": 1,
"lr": 1e-05,
"weight_decay": 0.01,
"max_grad_norm": 1.0,
"pretrain_train_samples": 72000,
"pretrain_validation_samples": 8000,
"pretrain_grad_accum_steps": 8,
"finetune_train_samples": 11491,
"finetune_validation_samples": 1642,
"finetune_grad_accum_steps": 1
}
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