[Model] Wire quant_config/prefix into input embeddings for GPTNeoX and Llama

[KKothuri]

Purpose

compressed-tensors supports weight-only WNA16-INT quantization of the input embedding (CompressedTensorsEmbeddingWNA16Int, added in #44340), but a VocabParallelEmbedding is only quantized if the model passes quant_config (and, for name-based targets, prefix) to it.

• GPTNeoX passed neither, so a checkpoint with a quantized embed_in silently fell back to an unquantized embedding and failed to load with KeyError: 'embed_in.weight_packed'.
• Llama passed quant_config but not prefix, so name-based targets (e.g. re:.*embed_tokens$) could not match (empty layer_name) and hit the same silent fallback: KeyError: 'embed_tokens.weight_packed'.

This passes quant_config and prefix to both input embeddings (3 lines). Class-based targets (["Embedding"]) already worked on Llama via class-name matching; this additionally makes name-based targets work and enables GPTNeoX at all.

Not a duplicate: related embedding-quant PRs exist (#42791 ModelOpt FP8/NVFP4 embedding methods, #41365 opt-in FP8 vocab embedding) but none addresses the compressed-tensors WNA16 input-embedding plumbing for these models.

Test Plan

New tests/quantization/test_quantized_embedding.py loads a tiny GPTNeoX checkpoint whose embed_in is WNA16-INT quantized (kkothuri/pythia-70m-emb-w4g64-ct, W4 group64), asserts it dispatches to CompressedTensorsEmbeddingWNA16Int, and smoke-tests generation. (The existing tests/kernels/quantization/test_quantized_embedding.py only covers the Triton kernel numerically, not model dispatch.)

pytest tests/quantization/test_quantized_embedding.py

Test Result

• Before: both GPTNeoX (pythia-1.4b) and Llama (Mistral-7B-v0.1) WNA16-embedding checkpoints fail to load with the KeyError above.
• After: both load and generate coherently.
• Accuracy (lm-eval, arc_easy + wikitext): embedding quant is ~lossless. pythia-1.4b W8-channel wikitext ppl 14.733 → 14.732, arc_easy 0.6048 → 0.6052; W4-group64 ppl → 14.752, arc_easy → 0.6061. On Mistral-7B (on top of W4A16 linears) adding W4-group64 embedding quant changes wikitext bits-per-byte by +0.46% with arc_easy flat.
• New test passes; pre-commit run on changed files is clean.

Note

The test fixture is currently hosted under a personal HF account (kkothuri/pythia-70m-emb-w4g64-ct); happy to re-host under nm-testing if maintainers prefer.

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This change was developed with AI assistance (Claude Code). All changed lines were reviewed by the submitter.

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