Commit History
13 days ago
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Add reference OpenVINO IRs
Verified signatureGenerated with: - transformers==5.10.4 - optimum-intel==2.3.0.dev0+1bf72b96 - openvino==2026.5.0-23376ddde167
21 days ago
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Add reference OpenVINO IRs
Generated with: - transformers==5.10.4 - optimum-intel==2.3.0.dev0+3329b15b - openvino==2026.5.0-23311-786052d995f (#1) - Add reference OpenVINO IRs (30035a5656876da49c80182f2ac6e32a06e8072d)4426d1a
30 days ago
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Add reference OpenVINO IRs
Verified signatureGenerated with: - transformers==5.10.4 - optimum-intel==2.3.0.dev0+e1c31ae1 - openvino==2026.4.0-22959-99c81491cc3-releases/2026/4f1b3cdd
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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)
Verified signaturea445c41