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

Commencez par exécuter la reproduction de safetensors avec les fichiers model.safetensors actuels et comparez-les aux commits 9ff478e2487b et 9f43072f6949. Inspectez ensuite utils/convert-ms-to-gguf-bitnet.py, en particulier SAFETENSORS_DATA_TYPES et les correspondances ffn_sub_norm/attn_sub_norm. C’est terminé lorsque vous avez vérifié que les checkpoints non nuls sont restaurés, que GGUF s’exécute sans sortie indésirable et que le chemin du convertisseur concerné est utilisable.

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