Model architectures for VLMs differ primarily in how visual and textual information is fused. Mid-fusion models use a pretrained vision encoder to convert images into visual tokens that are projected into a pretrained LLM’s embedding space, enabling cross-modal reasoning while leveraging components already trained on trillions of tokens. Early-fusion models process image patches and text tokens in a single model transformer, yielding richer joint representations but at significantly higher compute, memory, and data cost. We adopted a mid-fusion architecture as it offers a practical trade-off for building a performant model with modest resources.
量化将模型权重从 32/16 位数字压缩为 8 位 (int8) 或 4 位 (int4)。位数越少，文件越小，推理速度越快，但质量可能越低。，推荐阅读黑料获取更多信息
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The protection “is needed. It’s important,” said Allen. “Fungi play an important role in the ecosystem. We know a lot about fungi, but mycologists haven’t been invited to the table to share their knowledge.”，这一点在超级权重中也有详细论述