Commit History
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Make the fixture loadable on the whole supported transformers range
Verified signatureRegenerated with create_tiny_ltx23_model.py (marker_version 2). The previous revision was saved under transformers 5.x and inherited two version-dependent spellings from save_pretrained, both of which broke transformers 4.57.6: * tokenizer_class was recorded as `GemmaTokenizer` because on 5.x `GemmaTokenizerFast` is a deprecated alias of it. On 4.x that name is the sentencepiece class, which needs a tokenizer.model this fixture does not ship, so loading raised `ValueError: Either model_file or model_proto must be specified.` and the test_exporters_cli_tokenizers text-to-video / image-to-video cases failed. * text_encoder/model.safetensors keys carried an extra leading `model.` segment, which matches no rule in 4.x's Gemma3 _checkpoint_conversion_mapping, so the text encoder loaded silently with randomly initialised weights. Both are now normalised after saving. Verified on transformers 4.57.6, 5.5.4 and 5.10.4: the text encoder loads 51/51 params with 0 missing and 0 unexpected keys…ac56122
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Add tiny random LTX-2.3 fixture (derived from diffusers/LTX-2.3-Diffusers)
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