jingyaogong/siglip2-base-p32-256-ve

SigLIP2 ViT-B/32 Vision Encoder (256)

模型来源：google/siglip2-base-patch32-256

仅裁剪保留了 Vision Encoder 部分，去除了 Text Encoder 及其他无关权重，并以 float16 精度保存为 HuggingFace SiglipVisionModel 兼容的 safetensors 格式。

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Source: google/siglip2-base-patch32-256

Only the Vision Encoder is retained. The Text Encoder and all unrelated weights have been removed. Weights are saved in float16 precision as HuggingFace SiglipVisionModel-compatible safetensors format.

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Model Info

Item	Value
Architecture	SigLIP2 ViT-B/32 (fixed resolution)
Parameters	94.6M
Hidden Size	768
Layers	12
Patch Size	32
Input Resolution	256×256
Output Tokens	64 (8×8)
Weight Precision	float16
File Size	~180MB

Usage

from transformers import SiglipVisionModel, SiglipImageProcessor

model = SiglipVisionModel.from_pretrained("path_to/siglip2-base-p32-256-ve")
processor = SiglipImageProcessor.from_pretrained("path_to/siglip2-base-p32-256-ve")

inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)  # outputs.last_hidden_state: [B, 64, 768]