Reddit调查者称numbat检查点权重为生成所得
AI 总结
一名Reddit调查者称，burner22/numbat检查点中受测权重是确定性生成的，而非通过训练习得。调查者表示，使用SHA-256和NumPy PCG64逐位重建了全部633个受测张量，共11,374,080个数值；3.736亿个权重符号全部符合预测的伪随机序列，1.73亿个留出的NVFP4量化代码中有99.51%被重建。一个4.73B参数截断模型虽能运行，但只生成重复标点，无法形成有意义的语言。调查还发现嵌入中存在一些语义结构，但调查者表示这并不能使所重建的权重系列成为真正的训练权重。该分析没有确定检查点的创建者，也没有证明它与Anthropic存在任何联系。
I investigated burner22/numbat, a 7.72TB checkpoint claiming to be an internal Anthropic Mythos-class model.
My forensic findings show that the tested weights are deterministically generated, not learned through training. The checkpoint's claim to be a genuine trained model is not supported by this evidence.
Here's the proof:
Conclusion: This is a fake model checkpoint containing demonstrably generated weights. The analysis does not establish who created it or whether it has any connection to Anthropic.
Full forensic research, reconstruction scripts, and evidence:
https://huggingface.co/adityawakharkar/numbat-forensics
All findings are open for independent verification. submitted by /u/Appropriate-Try-1998
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