sglang_embedding_lora_test_adapter

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ash256
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Quick Summary

AI model with specialized capabilities.

Code Examples

Weight Shapestext
down_proj.lora_A: (8, 5632)
down_proj.lora_B: (2048, 8)
embed_tokens.lora_embedding_A: (8, 32000)
embed_tokens.lora_embedding_B: (2048, 8)
gate_proj.lora_A: (8, 2048)
gate_proj.lora_B: (5632, 8)
k_proj.lora_A: (8, 2048)
k_proj.lora_B: (256, 8)
lm_head.lora_A: (8, 2048)
lm_head.lora_B: (32000, 8)
o_proj.lora_A: (8, 2048)
o_proj.lora_B: (2048, 8)
q_proj.lora_A: (8, 2048)
q_proj.lora_B: (2048, 8)
up_proj.lora_A: (8, 2048)
up_proj.lora_B: (5632, 8)
v_proj.lora_A: (8, 2048)
v_proj.lora_B: (256, 8)
Usage with SGLangpython
# Used by: test/srt/lora/test_lora_hf_sgl_logprob_diff.py
# The adapter produces coherent outputs for meaningful CI/CD verification.
Usage with SGLangbash
python scripts/playground/lora/train_embedding_lora_adapter.py --num_train_steps 500

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