Fu DaiandClaude Opus 4.8
1a585693be
FastAPI service wrapping the Surya-OCR-2 model (datalab-to) served through vLLM: legacy /v1/api/ai/* endpoints, an OpenAI-compatible /v1/chat/completions endpoint, a coalescing request batcher, a local OCR CLI, Docker packaging, multilingual example outputs, and quantization/concurrency benchmarks. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
from transformers import PretrainedConfig
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from surya.common.s3 import S3DownloaderMixin
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class EfficientViTConfig(S3DownloaderMixin, PretrainedConfig):
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r"""
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```"""
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model_type = "efficientvit"
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def __init__(
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self,
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num_classes=2,
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num_channels=3,
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widths=(32, 64, 128, 256, 512),
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head_dim=32,
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num_stages=4,
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depths=(1, 1, 1, 6, 6),
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strides=(2, 2, 2, 2, 2),
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hidden_sizes=(32, 64, 160, 256),
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patch_size=(7, 7),
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hidden_dropout_prob=0.0,
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attention_probs_dropout_prob=0.0,
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classifier_dropout_prob=0.0,
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layer_norm_eps=1e-6,
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decoder_layer_hidden_size=128,
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decoder_hidden_size=512,
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semantic_loss_ignore_index=255,
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initializer_range=0.02,
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**kwargs,
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):
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super().__init__(**kwargs)
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self.num_classes = num_classes
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self.widths = widths
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self.head_dim = head_dim
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self.num_channels = num_channels
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self.num_stages = num_stages
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self.depths = depths
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self.strides = strides
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self.hidden_sizes = hidden_sizes
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self.patch_size = patch_size
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self.hidden_dropout_prob = hidden_dropout_prob
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self.attention_probs_dropout_prob = attention_probs_dropout_prob
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self.classifier_dropout_prob = classifier_dropout_prob
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self.layer_norm_eps = layer_norm_eps
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self.decoder_hidden_size = decoder_hidden_size
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self.decoder_layer_hidden_size = decoder_layer_hidden_size
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self.semantic_loss_ignore_index = semantic_loss_ignore_index
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self.initializer_range = initializer_range |