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* Fix FastSentenceTransformer Qwen embedding preprocessing * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Document Transformer.load embedding modality fix for #6881 * Harden #6881 fix and add forwards/backwards-compatible regression tests * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fall back to Transformer constructor on legacy sentence-transformers without Hub-capable load * Mirror legacy sentence-transformers fallback in embedding-parity tripwire test * Tighten #6881 comments and docstrings * Skip embedding-parity test on CPU-only runners since FastSentenceTransformer requires CUDA * Honor the transformer module's saved subfolder when loading modules.json records a path for the Transformer module (root for decoder embedders like Qwen3-Embedding, 0_Transformer for the classic layout). Pooling/Normalize already load from their saved path; thread the same path into Transformer.load as subfolder so config and tokenizer resolve like stock ST. stays a no-op, so single-module models are unchanged. * Make embedding-parity test bf16-aware fp16 overflows to NaN on bf16-native embedders such as EmbeddingGemma (Gemma3), producing a false parity failure. Prefer bf16 when the GPU supports it so the tripwire can guard the full documented embedding matrix (Qwen3-Embedding, EmbeddingGemma, BGE-M3, all-MiniLM, GTE-ModernBERT), not just fp16-safe models. --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: danielhanchen <danielhanchen@gmail.com> |
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| .. | ||
| __init__.py | ||
| _fetch.py | ||
| test_bitsandbytes_pinned_symbols.py | ||
| test_peft_pinned_symbols.py | ||
| test_sentence_transformers_pinned_symbols.py | ||
| test_transformers_pinned_symbols.py | ||
| test_trl_fake_train_cpu.py | ||
| test_trl_grpo_fake_run.py | ||
| test_trl_grpo_pinned_symbols.py | ||
| test_unsloth_zoo_save_merged_pinned_symbols.py | ||