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Current bitnet-b1.58-2B-4T checkpoints contain all-zero MLP weight tensors (model generates garbage)

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难度
4/5
预计耗时
3-5 天
新手友好度
45/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
冷清
技术栈
cpp, python, pytorch

调研方向

首先,针对当前的 model.safetensors 文件运行 safetensors 复现,并将其与提交 9ff478e2487b 和 9f43072f6949 进行比较。然后检查 utils/convert-ms-to-gguf-bitnet.py,尤其是 SAFETENSORS_DATA_TYPES 以及 ffn_sub_norm/attn_sub_norm 映射。完成的标准是:已验证非零 checkpoint 得到恢复,GGUF 运行时不会产生垃圾输出,并且受影响的转换器路径可用。

由索引模型根据 Issue 内容生成。

描述

Current bitnet-b1.58-2B-4T checkpoints contain all-zero MLP weight tensors (model generates garbage)

Summary

The current releases of microsoft/bitnet-b1.58-2B-4T, microsoft/bitnet-b1.58-2B-4T-bf16, and microsoft/bitnet-b1.58-2B-4T-gguf contain weight tensors that are entirely zero in several layers. Running the GGUF through bitnet.cpp produces repeated garbage tokens, consistent with the zeroed weights. The original releases (April 2025) are intact — the breakage was introduced by a later re-upload ("Update Model").

Affected repos / files (current main)
Repo File Size
microsoft/bitnet-b1.58-2B-4T model.safetensors (U8 "quantized" format) 1,178,623,988 B
microsoft/bitnet-b1.58-2B-4T-bf16 model.safetensors 4,825,679,400 B
microsoft/bitnet-b1.58-2B-4T-gguf ggml-model-i2_s.gguf 1,187,801,280 B
Evidence (verified 2026-08-10, direct tensor inspection via safetensors/torch)

microsoft/bitnet-b1.58-2B-4T-bf16 (current):

model.layers.0.mlp.down_proj.weight   [2560, 6912]  min=0 max=0 mean=0 nonzero=0
model.layers.0.mlp.gate_proj.weight   [6912, 2560]  min=0 max=0 mean=0 nonzero=0
model.layers.0.mlp.up_proj.weight     [6912, 2560]  min=0 max=0 mean=0 nonzero=0
model.layers.1.mlp.up_proj.weight     nonzero=0 / 17,694,720
model.layers.10.mlp.up_proj.weight    nonzero=0 / 17,694,720
model.layers.2.mlp.up_proj.weight     nonzero=6,733,450 (has data — only some layers zeroed)

microsoft/bitnet-b1.58-2B-4T (current, U8):

model.layers.0.mlp.down_proj.weight   uint8, all 0x00; weight_scale = 0.0
model.layers.0.mlp.gate_proj.weight   uint8, all 0x00
model.layers.0.self_attn.q_proj.weight  (valid 2-bit packed ternary data)

microsoft/bitnet-b1.58-2B-4T-gguf (current):

blk.0.ffn_up   I2_S, nonzero=0 / 4,423,712
blk.2.ffn_up   I2_S, nonzero=0 / 4,423,712
blk.1.ffn_up   I2_S, nonzero=4,383,655 (has data)

Note the zeroed layers differ between the bf16 repo ({0,1,10}) and the GGUF repo ({0,2}) — the GGUF was evidently built from a different broken snapshot.

Reproduction (5 lines):

from safetensors import safe_open
with safe_open("model.safetensors", framework="pt") as f:
    w = f.get_tensor("model.layers.0.mlp.up_proj.weight")
    print((w != 0).sum().item(), "/", w.numel())   # -> 0 / 17694720

Running the current ggml-model-i2_s.gguf through bitnet.cpp (llama-cli, temp=0) outputs only ? tokens — the model is non-functional.

History / root cause

The original releases are intact and work:

  • microsoft/bitnet-b1.58-2B-4T commit 9ff478e2487b → model.safetensors = 1,835,292,112 B (original)
  • microsoft/bitnet-b1.58-2B-4T-gguf commit 9f43072f6949 → ggml-model-i2_s.gguf = 1,844,472,032 B (original)

The re-upload commit 24edd43d41aa ("Update Model") replaced the file with the broken 1.18 GB version.

Secondary issue (tooling)

The new checkpoint format is not supported by any current converter:

  • bitnet.cpp utils/convert-ms-to-gguf-bitnet.py fails with KeyError: 'U8' in SAFETENSORS_DATA_TYPES (new uint8 dtype not registered)
  • upstream llama.cpp convert_hf_to_gguf.py cannot map the new ffn_sub_norm / attn_sub_norm tensor names
  • Only the old-format files (original bf16 / original GGUF) can be converted and run today
Suggested fix
  1. Restore the correct weights (re-upload from 9ff478e2 / 9f43072f), or fix whatever produced the zeroed tensors
  2. Regenerate the GGUF from a verified-good checkpoint
  3. Register the U8 dtype (and ffn_sub_norm mapping) in bitnet.cpp's converter so the new format is usable
主要语言
C++
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