Current bitnet-b1.58-2B-4T checkpoints contain all-zero MLP weight tensors (model generates garbage)
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Description
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-4Tcommit9ff478e2487b→model.safetensors= 1,835,292,112 B (original)microsoft/bitnet-b1.58-2B-4T-ggufcommit9f43072f6949→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.pyfails withKeyError: 'U8'inSAFETENSORS_DATA_TYPES(newuint8dtype not registered) - upstream llama.cpp
convert_hf_to_gguf.pycannot map the newffn_sub_norm/attn_sub_normtensor names - Only the old-format files (original bf16 / original GGUF) can be converted and run today
Suggested fix
- Restore the correct weights (re-upload from
9ff478e2/9f43072f), or fix whatever produced the zeroed tensors - Regenerate the GGUF from a verified-good checkpoint
- Register the
U8dtype (andffn_sub_normmapping) in bitnet.cpp's converter so the new format is usable
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by running the safetensors reproduction against the current model.safetensors files and compare them with commits 9ff478e2487b and 9f43072f6949. Then inspect utils/convert-ms-to-gguf-bitnet.py, especially SAFETENSORS_DATA_TYPES and the ffn_sub_norm/attn_sub_norm mappings. Done means verified nonzero checkpoints are restored, the GGUF runs without garbage output, and the affected converter path is usable.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python, pytorch
- Domain
- machine-learning, tooling
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100