# Unsloth 环境标志

<table><thead><tr><th width="397.4666748046875">环境变量</th><th>用途</th><th data-hidden></th></tr></thead><tbody><tr><td><code>os.environ["UNSLOTH_RETURN_LOGITS"] = "1"</code></td><td>强制返回logits——如果需要logits进行评估时很有用。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_COMPILE_DISABLE"] = "1"</code></td><td>禁用自动编译器。用于调试不正确的微调结果可能很有用。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_DISABLE_FAST_GENERATION"] = "1"</code></td><td>为通用模型禁用快速生成。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_ENABLE_LOGGING"] = "1"</code></td><td>启用自动编译器日志记录——有助于查看哪些函数已被编译或未被编译。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_FORCE_FLOAT32"] = "1"</code></td><td>在float16机器上使用float32而不是float16混合精度。对于Gemma 3很有用。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_STUDIO_DISABLED"] = "1"</code></td><td>禁用附加功能。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_COMPILE_DEBUG"] = "1"</code></td><td>开启极其详细的 <code>torch.compile</code>日志。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_COMPILE_MAXIMUM"] = "0"</code></td><td>启用最大化的 <code>torch.compile</code>优化——不推荐。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_COMPILE_IGNORE_ERRORS"] = "1"</code></td><td>可以关闭此项以启用全图解析。</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_FULLGRAPH"] = "0"</code></td><td>启用 <code>torch.compile</code> 全图模式</td><td></td></tr><tr><td><code>os.environ["UNSLOTH_DISABLE_AUTO_UPDATES"] = "1"</code></td><td>强制不更新 <code>unsloth-zoo</code></td><td></td></tr></tbody></table>

另一种可能性是我们上传的模型已损坏，但不太可能。尝试以下操作：

```python
model, tokenizer = FastVisionModel.from_pretrained(
    "Qwen/Qwen2-VL-7B-Instruct",
    use_exact_model_name = True,
)
```


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