Remove static pretrained maps from the library's internals (#29112)
* [test_all] Remove static pretrained maps from the library's internals * Deprecate archive maps instead of removing them * Revert init changes * [test_all] Deprecate instead of removing * [test_all] PVT v2 support * [test_all] Tests should all pass * [test_all] Style * Address review comments * Update src/transformers/models/deprecated/_archive_maps.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/deprecated/_archive_maps.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * [test_all] trigger tests * [test_all] LLAVA * [test_all] Bad rebase --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
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@@ -32,7 +32,6 @@ if is_tf_available():
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from transformers.modeling_tf_utils import keras
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from transformers.models.esm.modeling_tf_esm import (
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TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
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TFEsmForMaskedLM,
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TFEsmForSequenceClassification,
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TFEsmForTokenClassification,
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@@ -253,9 +252,9 @@ class TFEsmModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
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@slow
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def test_model_from_pretrained(self):
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for model_name in TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
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model = TFEsmModel.from_pretrained(model_name)
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self.assertIsNotNone(model)
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model_name = "facebook/esm2_t6_8M_UR50D"
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model = TFEsmModel.from_pretrained(model_name)
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self.assertIsNotNone(model)
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@unittest.skip("Protein models do not support embedding resizing.")
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def test_resize_token_embeddings(self):
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