Instructions to use Yechao/MemGhost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Yechao/MemGhost with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B") model = PeftModel.from_pretrained(base_model, "Yechao/MemGhost") - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from Yechao/MemGhost: direct link, hf CLI and curl.
- Browser
- Download file 754 Bytes
-
https://huggingface.co/Yechao/MemGhost/resolve/main/adapter_config.json
- Command line
-
hf download hf://Yechao/MemGhost/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/Yechao/MemGhost/resolve/main/adapter_config.json
754 Bytes
| {"alpha_pattern": {}, "auto_mapping": null, "base_model_name_or_path": "Qwen/Qwen3-4B", "bias": "none", "corda_config": null, "eva_config": null, "exclude_modules": null, "fan_in_fan_out": false, "inference_mode": true, "init_lora_weights": true, "layer_replication": null, "layers_pattern": null, "layers_to_transform": null, "loftq_config": {}, "lora_alpha": 128, "lora_bias": false, "lora_dropout": 0.0, "megatron_config": null, "megatron_core": "megatron.core", "modules_to_save": null, "peft_type": "LORA", "r": 64, "rank_pattern": {}, "revision": null, "target_modules": ["o_proj", "up_proj", "gate_proj", "v_proj", "k_proj", "q_proj", "down_proj"], "task_type": "CAUSAL_LM", "trainable_token_indices": null, "use_dora": false, "use_rslora": false} |