* remove from base

* delete

* fetcher fix

* missing values

* update

* is decoder missing

* forgot to add

* add special tokens with default `None` in text models

* fsmt has unused subconfig, fix it!

* update

* fix

* add missig token id defaults

* fix more tests

* tie_word_embeddings

* tiny fixes

* more test fixes

* fix docstrings

* fix copies

* fix style?

* fix copied again

* fix copies

* fix examples

* delete left over print stmt

* splitnter

* this defi will fix a bunch decoder-only models

* make style

* fix copies

* not all models are supposed to have an attr for `tie_word_embeddings`!

* comment out

* fix

* more fixes

* fix copies

* docstring and non-model tests

* update

* fix repo consistency

* style

* fix

* revert

* remove unused attr

* fix repo

* fix test

* fix a few tests, more tests

* fix gemma & llava

* style

* gemma3n also

* new models as well

* skip the test

---------

Co-authored-by: ydshieh <[email protected]>

PR huggingface#41541 refactored `tie_word_embeddings` handling (among other things)
which subtly broke detection of T5 v1.1 vs. original detection. As a
consequence, decoder output scaling was always applied, regardless of
T5 version.

This is resolved by using the correct value for `tie_word_embeddings`.

**Testing:**

This was not covered by the tests since the tests instantiate the config
once and modify attributes on the config. This is problematic since all
the decision logic is happening in `T5Config.__init__`. This was addressed
by having a specific `get_config_v1_1` method that initializes the
config as if it were coming from a v1.1 model (e.g., flan-t5).

## Summary
<!--- This is a required section; please describe the main purpose of
this proposed code change. --->
Fix multiple failing monkey_patch tests for transformers v5. The tests
failed because of
huggingface/transformers#41541.

These changes are backward compatible.

This change fixes the following failing tests:
```
FAILED test/transformers/test_monkey_patch.py::test_apply_liger_kernel_to_instance_for_qwen3_vl_moe_for_conditional_generation - AttributeError: 'Qwen3VLMoeTextConfig' object has no attribute 'pad_token_id'
FAILED test/transformers/test_monkey_patch.py::test_apply_liger_kernel_to_instance_for_qwen3_vl_moe - AttributeError: 'Qwen3VLMoeTextConfig' object has no attribute 'pad_token_id'
FAILED test/transformers/test_monkey_patch.py::test_apply_liger_kernel_to_instance_for_qwen3_vl_moe_text - AttributeError: 'Qwen3VLMoeTextConfig' object has no attribute 'pad_token_id'
FAILED test/transformers/test_monkey_patch.py::test_apply_liger_kernel_to_instance_for_llama4_for_conditional_generation - AttributeError: 'Llama4Config' object has no attribute 'pad_token_id'
FAILED test/transformers/test_monkey_patch.py::test_apply_liger_kernel_to_instance_for_glm4v - AttributeError: 'Glm4vTextConfig' object has no attribute 'pad_token_id'
```


Fixes #1059.

<!---
## Details
This is an optional section; is there anything specific that reviewers
should be aware of?
--->

## Testing Done
<!--- This is a required section; please describe how this change was
tested. --->

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- [ ] run `make test` to ensure correctness
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- [ ] run `make test-convergence` to ensure convergence

* Fix T5 v1.1 detection

PR #41541 refactored `tie_word_embeddings` handling (among other things)
which subtly broke detection of T5 v1.1 vs. original detection. As a
consequence, decoder output scaling was always applied, regardless of
T5 version.

This is resolved by using the correct value for `tie_word_embeddings`.

**Testing:**

This was not covered by the tests since the tests instantiate the config
once and modify attributes on the config. This is problematic since all
the decision logic is happening in `T5Config.__init__`. This was addressed
by having a specific `get_config_v1_1` method that initializes the
config as if it were coming from a v1.1 model (e.g., flan-t5).

* Make repo consistent

* Make repo consistent

* mt5 isn't copied from t5 anymore

---------

Co-authored-by: nemo <[email protected]>
Co-authored-by: raushan <[email protected]>

* Fix T5 v1.1 detection

PR #41541 refactored `tie_word_embeddings` handling (among other things)
which subtly broke detection of T5 v1.1 vs. original detection. As a
consequence, decoder output scaling was always applied, regardless of
T5 version.

This is resolved by using the correct value for `tie_word_embeddings`.

**Testing:**

This was not covered by the tests since the tests instantiate the config
once and modify attributes on the config. This is problematic since all
the decision logic is happening in `T5Config.__init__`. This was addressed
by having a specific `get_config_v1_1` method that initializes the
config as if it were coming from a v1.1 model (e.g., flan-t5).

* Make repo consistent

* Make repo consistent

* mt5 isn't copied from t5 anymore

---------

Co-authored-by: nemo <[email protected]>
Co-authored-by: raushan <[email protected]>

* Fix T5 v1.1 detection

PR #41541 refactored `tie_word_embeddings` handling (among other things)
which subtly broke detection of T5 v1.1 vs. original detection. As a
consequence, decoder output scaling was always applied, regardless of
T5 version.

This is resolved by using the correct value for `tie_word_embeddings`.

**Testing:**

This was not covered by the tests since the tests instantiate the config
once and modify attributes on the config. This is problematic since all
the decision logic is happening in `T5Config.__init__`. This was addressed
by having a specific `get_config_v1_1` method that initializes the
config as if it were coming from a v1.1 model (e.g., flan-t5).

* Make repo consistent

* Make repo consistent

* mt5 isn't copied from t5 anymore

---------

Co-authored-by: nemo <[email protected]>
Co-authored-by: raushan <[email protected]>

* Fix T5 v1.1 detection

PR #41541 refactored `tie_word_embeddings` handling (among other things)
which subtly broke detection of T5 v1.1 vs. original detection. As a
consequence, decoder output scaling was always applied, regardless of
T5 version.

This is resolved by using the correct value for `tie_word_embeddings`.

**Testing:**

This was not covered by the tests since the tests instantiate the config
once and modify attributes on the config. This is problematic since all
the decision logic is happening in `T5Config.__init__`. This was addressed
by having a specific `get_config_v1_1` method that initializes the
config as if it were coming from a v1.1 model (e.g., flan-t5).

* Make repo consistent

* Make repo consistent

* mt5 isn't copied from t5 anymore

---------

Co-authored-by: nemo <[email protected]>
Co-authored-by: raushan <[email protected]>

* Fix T5 v1.1 detection

PR huggingface#41541 refactored `tie_word_embeddings` handling (among other things)
which subtly broke detection of T5 v1.1 vs. original detection. As a
consequence, decoder output scaling was always applied, regardless of
T5 version.

This is resolved by using the correct value for `tie_word_embeddings`.

**Testing:**

This was not covered by the tests since the tests instantiate the config
once and modify attributes on the config. This is problematic since all
the decision logic is happening in `T5Config.__init__`. This was addressed
by having a specific `get_config_v1_1` method that initializes the
config as if it were coming from a v1.1 model (e.g., flan-t5).

* Make repo consistent

* Make repo consistent

* mt5 isn't copied from t5 anymore

---------

Co-authored-by: nemo <[email protected]>
Co-authored-by: raushan <[email protected]>