unsloth/tests/test_model_registry.py
Daniel Han ad9976450d Qwen 3, Bug Fixes (#2445)
* bug fix #2008 (#2039)

* fix (#2051)

* Update loader.py

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* more prints

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* LoRA 16bit fix

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* move forced float32

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* move print

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* disable bfloat16

* Fix forced float32

* move float32

* Ensure trust_remote_code propegates down to unsloth_compile_transformers (#2075)

* Update _utils.py

* Show both `peft_error` and `autoconfig_error`, not just `autoconfig_error` (#2080)

When loading a PEFT model fails, only the `autoconfig_error` is shown. Instead of the `peft_error`, which is what really matters when we're trying to load a PEFT adapter, the user will see something like this:

```
RuntimeError: Unrecognized model in my_model. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: albert, align, altclip, ...
```

This PR just changes it so `autoconfig_error` and `peft_error` are both displayed.

* fix error message (#2046)

* Update vision.py

* Update _utils.py

* Update pyproject.toml

* Update __init__.py

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* Update rl_replacements.py

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* Remove double generate patch

* Update vision.py

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* Update mapper.py

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* fix: config.torch_dtype in LlamaModel_fast_forward_inference (#2091)

* fix: config.torch_dtype in LlamaModel_fast_forward_inference

* Update llama.py

* update for consistency

---------

Co-authored-by: Daniel Han <danielhanchen@gmail.com>

* versioning

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* model_type_arch

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* Update loader.py

* check

* Update _utils.py

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* Remove prints

* Update README.md

typo

* Update _utils.py

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* versioning

* Update _utils.py

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* Update llama.py

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* Update vision.py

* HF Transfer

* fix(utils): add missing importlib import to fix NameError (#2134)

This commit fixes a NameError that occurs when `importlib` is referenced in _utils.py
without being imported, especially when UNSLOTH_USE_MODELSCOPE=1 is enabled.
By adding the missing import statement, the code will no longer throw a NameError.

* Add QLoRA Train and Merge16bit Test (#2130)

* add reference and unsloth lora merging tests

* add test / dataset printing to test scripts

* allow running tests from repo root

* add qlora test readme

* more readme edits

* ruff formatting

* additional readme comments

* forgot to add actual tests

* add apache license

* Update pyproject.toml

* Update vision.py

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* Update loader.py

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* Revert

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* Bug fix

* Update mapper.py

* check SDPA for Mistral 3, Pixtral

* Update vision.py

* Versioning

* Update rl_replacements.py

* Update README.md

* add model registry

* move hf hub utils to unsloth/utils

* refactor global model info dicts to dataclasses

* fix dataclass init

* fix llama registration

* remove deprecated key function

* start registry reog

* add llama vision

* quant types -> Enum

* remap literal quant types to QuantType Enum

* add llama model registration

* fix quant tag mapping

* add qwen2.5 models to registry

* add option to include original model in registry

* handle quant types per model size

* separate registration of base and instruct llama3.2

* add QwenQVQ to registry

* add gemma3 to registry

* add phi

* add deepseek v3

* add deepseek r1 base

* add deepseek r1 zero

* add deepseek distill llama

* add deepseek distill models

* remove redundant code when constructing model names

* add mistral small to registry

* rename model registration methods

* rename deepseek registration methods

* refactor naming for mistral and phi

* add global register models

* refactor model registration tests for new registry apis

* add model search method

* remove deprecated registration api

* add quant type test

* add registry readme

* make llama registration more specific

* clear registry when executing individual model registration file

* more registry readme updates

* Update _auto_install.py

* Llama4

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* Synthetic data

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* Update pyproject.toml

* Delete .gitignore

---------

Co-authored-by: Mukkesh Ganesh <mukmckenzie@gmail.com>
Co-authored-by: Kareem <81531392+KareemMusleh@users.noreply.github.com>
Co-authored-by: Xander Hawthorne <167850078+CuppaXanax@users.noreply.github.com>
Co-authored-by: Isaac Breen <isaac.breen@icloud.com>
Co-authored-by: lurf21 <93976703+lurf21@users.noreply.github.com>
Co-authored-by: Jack Shi Wei Lun <87535974+jackswl@users.noreply.github.com>
Co-authored-by: naliazheli <nalia0316@gmail.com>
Co-authored-by: jeromeku <jerome.ku@gmail.com>
Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
2025-04-30 22:38:39 -07:00

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Python

"""
Test model registration methods
Checks that model registration methods work for respective models as well as all models
The check is performed
- by registering the models
- checking that the instantiated models can be found on huggingface hub by querying for the model id
"""
from dataclasses import dataclass
import pytest
from huggingface_hub import ModelInfo as HfModelInfo
from unsloth.registry import register_models, search_models
from unsloth.registry._deepseek import register_deepseek_models
from unsloth.registry._gemma import register_gemma_models
from unsloth.registry._llama import register_llama_models
from unsloth.registry._mistral import register_mistral_models
from unsloth.registry._phi import register_phi_models
from unsloth.registry._qwen import register_qwen_models
from unsloth.registry.registry import MODEL_REGISTRY, QUANT_TAG_MAP, QuantType
from unsloth.utils.hf_hub import get_model_info
MODEL_NAMES = [
"llama",
"qwen",
"mistral",
"phi",
"gemma",
"deepseek",
]
MODEL_REGISTRATION_METHODS = [
register_llama_models,
register_qwen_models,
register_mistral_models,
register_phi_models,
register_gemma_models,
register_deepseek_models,
]
@dataclass
class ModelTestParam:
name: str
register_models: callable
def _test_model_uploaded(model_ids: list[str]):
missing_models = []
for _id in model_ids:
model_info: HfModelInfo = get_model_info(_id)
if not model_info:
missing_models.append(_id)
return missing_models
TestParams = [
ModelTestParam(name, models)
for name, models in zip(MODEL_NAMES, MODEL_REGISTRATION_METHODS)
]
# Test that model registration methods register respective models
@pytest.mark.parametrize("model_test_param", TestParams, ids=lambda param: param.name)
def test_model_registration(model_test_param: ModelTestParam):
MODEL_REGISTRY.clear()
registration_method = model_test_param.register_models
registration_method()
registered_models = MODEL_REGISTRY.keys()
missing_models = _test_model_uploaded(registered_models)
assert not missing_models, (
f"{model_test_param.name} missing following models: {missing_models}"
)
def test_all_model_registration():
register_models()
registered_models = MODEL_REGISTRY.keys()
missing_models = _test_model_uploaded(registered_models)
assert not missing_models, f"Missing following models: {missing_models}"
def test_quant_type():
# Test that the quant_type is correctly set for model paths
# NOTE: for models registered under org="unsloth" with QuantType.NONE aliases QuantType.UNSLOTH
dynamic_quant_models = search_models(quant_types=[QuantType.UNSLOTH])
assert all(m.quant_type == QuantType.UNSLOTH for m in dynamic_quant_models)
quant_tag = QUANT_TAG_MAP[QuantType.UNSLOTH]
assert all(quant_tag in m.model_path for m in dynamic_quant_models)