🛠️Unsloth Environment Flags

Advanced flags which might be useful if you see breaking finetunes, or you want to turn stuff off.

Environment variable	Purpose
os.environ["UNSLOTH_RETURN_LOGITS"] = "1"	Forcibly returns logits - useful for evaluation if logits are needed.
os.environ["UNSLOTH_COMPILE_DISABLE"] = "1"	Disables auto compiler. Could be useful to debug incorrect finetune results.
os.environ["UNSLOTH_DISABLE_FAST_GENERATION"] = "1"	Disables fast generation for generic models.
os.environ["UNSLOTH_ENABLE_LOGGING"] = "1"	Enables auto compiler logging - useful to see which functions are compiled or not.
os.environ["UNSLOTH_FORCE_FLOAT32"] = "1"	On float16 machines, use float32 and not float16 mixed precision. Useful for Gemma 3.
os.environ["UNSLOTH_STUDIO_DISABLED"] = "1"	Disables extra features.
os.environ["UNSLOTH_COMPILE_DEBUG"] = "1"	Turns on extremely verbose torch.compilelogs.
os.environ["UNSLOTH_COMPILE_MAXIMUM"] = "0"	Enables maximum torch.compileoptimizations - not recommended.
os.environ["UNSLOTH_COMPILE_IGNORE_ERRORS"] = "1"	Can turn this off to enable fullgraph parsing.
os.environ["UNSLOTH_FULLGRAPH"] = "0"	Enable torch.compile fullgraph mode
os.environ["UNSLOTH_DISABLE_AUTO_UPDATES"] = "1"	Forces no updates to unsloth-zoo

Another possiblity is maybe the model uploads we uploaded are corrupted, but unlikely. Try the following:

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