huggingface config_error ai_generated true

RuntimeError: You are trying to train a 4-bit model but you have set `inference_mode=True`. Set `inference_mode=False` for training.

ID: huggingface/peft-4bit-inference-mode

Also available as: JSON · Markdown · 中文

98%Fix Rate

88%Confidence

1Evidence

2023-09-10First Seen

Version Compatibility

Version	Status	Introduced	Deprecated	Notes
peft>=0.5.0	active	—	—	—
transformers>=4.31.0	active	—	—	—
bitsandbytes>=0.41.0	active	—	—	—

Root Cause

When using PEFT with a 4-bit quantized base model, the `inference_mode` flag in LoRA configuration must be False for training, but was set to True.

generic

中文

当使用 PEFT 与 4-bit 量化基础模型时，LoRA 配置中的 `inference_mode` 标志在训练时必须为 False，但被设置为 True。

Official Documentation

https://huggingface.co/docs/peft/v0.6.0/en/developer_guides/quantization#4-bit-models

Workarounds

98% success Set `inference_mode=False` in the LoRA configuration: `lora_config = LoraConfig(r=8, lora_alpha=32, inference_mode=False)`
```
Set `inference_mode=False` in the LoRA configuration: `lora_config = LoraConfig(r=8, lora_alpha=32, inference_mode=False)`
```
95% success If using the PEFT model directly, call `model.train()` and ensure the config was created with `inference_mode=False`. Example: `peft_config = LoraConfig.from_pretrained('path')` then modify `peft_config.inference_mode = False` before creating the model.
```
If using the PEFT model directly, call `model.train()` and ensure the config was created with `inference_mode=False`. Example: `peft_config = LoraConfig.from_pretrained('path')` then modify `peft_config.inference_mode = False` before creating the model.
```

中文步骤

在 LoRA 配置中设置 `inference_mode=False`：`lora_config = LoraConfig(r=8, lora_alpha=32, inference_mode=False)`

如果直接使用 PEFT 模型，调用 `model.train()` 并确保配置初始时设置了 `inference_mode=False`。示例：`peft_config = LoraConfig.from_pretrained('path')` 然后修改 `peft_config.inference_mode = False` 再创建模型。

Dead Ends

Common approaches that don't work:

85% fail
The error is specifically about the LoRA `inference_mode` parameter, not the model loading quantization. The LoRA config must be explicitly updated.
90% fail
The `inference_mode` flag in the LoRA config is separate from the model's training state. `model.train()` does not affect PEFT's internal configuration.