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[QUANT] Add GPTQModel Dynamic Quantization + lm_head Quantization (#3790)

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Signed-off-by: ZX-ModelCloud <zx@modelcloud.ai>
Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai>
This commit is contained in:
Qubitium-ModelCloud
2025-03-05 17:11:00 +08:00
committed by GitHub
parent 583d6af71b
commit 56a724eba3
56 changed files with 1988 additions and 282 deletions
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6
python/sglang/srt/models/gemma2_reward.py
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@@ -22,6 +22,7 @@ from sglang.srt.layers.pooler import EmbeddingPoolerOutput, Pooler, PoolingType
from sglang.srt.layers.quantization.base_config import QuantizationConfig
from sglang.srt.model_executor.forward_batch_info import ForwardBatch
from sglang.srt.models.gemma2 import Gemma2ForCausalLM, Gemma2Model
from sglang.srt.utils import add_prefix
class Gemma2ForSequenceClassification(nn.Module):
@@ -29,12 +30,15 @@ class Gemma2ForSequenceClassification(nn.Module):
self,
config: Gemma2Config,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
) -> None:
super().__init__()
self.config = config
self.quant_config = quant_config
self.num_labels = config.num_labels
self.model = Gemma2Model(config, quant_config=quant_config)
self.model = Gemma2Model(
config, quant_config=quant_config, prefix=add_prefix("model", prefix)
)
self.score = nn.Linear(config.hidden_size, self.num_labels, bias=False)
self.pooler = Pooler(pooling_type=PoolingType.LAST, normalize=False)