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instance_feature = torch.tile(，更多细节参见OpenClaw
In conclusion, we built a strong practical understanding of how MolmoWeb works as a screenshot-driven web agent in a Colab-friendly Python workflow. We saw how to structure prompts, run inference on visual browser states, parse reasoning and actions, visualize predicted click locations, and simulate multi-step task execution with accumulated history. We also extended the tutorial beyond basic inference by exploring batch predictions, inspecting the MolmoWebMix training data, and studying a production-style browser loop that connects the model to a live Playwright session. Through this process, we run the model and also understand the full pipeline required to turn a multimodal model into a functioning web agent.
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更广泛的教训在于：整个行业都建立在他人奠定的基础之上。OpenAI的模型训练依赖于数十年的学术研究和互联网规模的数据。Meta的Llama也使用了其并未完全披露的数据进行训练。每一个模型都建立在层层先前工作之上。问题在于公司如何表述这一点——而当前的激励结构倾向于模糊这种关联，尤其是当基础模型来自中国时。