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[Model][1/N] Automatic conversion of CrossEncoding model (#20012)

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Signed-off-by: wang.yuqi <noooop@126.com>
This commit is contained in:
wang.yuqi
2025-06-27 12:10:04 +08:00
committed by GitHub
parent e110930680
commit cd4cfee689
5 changed files with 239 additions and 167 deletions
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11
tests/models/language/pooling/mteb_utils.py
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@@ -43,7 +43,7 @@ class VllmMtebEncoder(mteb.Encoder):
# issues by randomizing the order.
r = self.rng.permutation(len(sentences))
sentences = [sentences[i] for i in r]
outputs = self.model.encode(sentences, use_tqdm=False)
outputs = self.model.embed(sentences, use_tqdm=False)
embeds = np.array(outputs)
embeds = embeds[np.argsort(r)]
return embeds
@@ -250,16 +250,19 @@ def mteb_test_rerank_models(hf_runner,
with vllm_runner(model_info.name,
task="score",
max_model_len=None,
max_num_seqs=8,
**vllm_extra_kwargs) as vllm_model:
model_config = vllm_model.model.llm_engine.model_config
if model_info.architecture:
assert (model_info.architecture
in vllm_model.model.llm_engine.model_config.architectures)
assert (model_info.architecture in model_config.architectures)
assert model_config.hf_config.num_labels == 1
vllm_main_score = run_mteb_rerank(VllmMtebEncoder(vllm_model),
tasks=MTEB_RERANK_TASKS,
languages=MTEB_RERANK_LANGS)
vllm_dtype = vllm_model.model.llm_engine.model_config.dtype
vllm_dtype = model_config.dtype
with hf_runner(model_info.name, is_cross_encoder=True,
dtype="float32") as hf_model: