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bff06c9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | """GreenLeaf Law Embed — model configuration.
A bidirectional transformer encoder built on the Qwen3 backbone,
specialized for legal-domain dense retrieval and text embedding.
"""
from transformers.models.qwen3.configuration_qwen3 import Qwen3Config
class GreenLeafEmbedConfig(Qwen3Config):
"""Configuration class for GreenLeaf law embedding models.
Inherits the Qwen3 architecture and applies the following
modifications for dense embedding tasks:
- All transformer layers use bidirectional (non-causal) attention
- KV caching is disabled (embedding models don't need it)
- Sliding window is disabled — every token attends to every token
"""
model_type = "greenleaf_embed"
def __init__(
self,
use_bidirectional_attention: bool = True,
use_cache: bool = False,
use_sliding_window: bool = False,
**kwargs,
):
kwargs["use_bidirectional_attention"] = use_bidirectional_attention
kwargs["use_cache"] = use_cache
kwargs["use_sliding_window"] = use_sliding_window
super().__init__(**kwargs)
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