Qwen 2.5 32B Instruct β Lossless Compressed
61.00 GB β 40.30 GB (34% smaller). Bit-identical weights. Drop-in replacement.
Use it in 2 lines
pip install "bigsmall>=3.14.1"
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("wpferrell/qwen2.5-32b-instruct-bigsmall")
It works exactly like loading the original model. No code changes needed.
Size comparison
| Size | |
|---|---|
| Original (Qwen/Qwen2.5-32B-Instruct) | 61.00 GB |
| This compressed version | 40.30 GB |
| Saved | 20.70 GB (34%) |
What "lossless" means
Every weight is mathematically identical to the original model.
- Not quantized. Quantization rounds weights and changes model behaviour.
- Not pruned. Pruning removes parts of the model.
- Bit-for-bit identical. md5 is verified on every tensor at decompression.
Low-VRAM streaming
from bigsmall import BigSmallStreamingModel
model = BigSmallStreamingModel.from_pretrained(
"wpferrell/qwen2.5-32b-instruct-bigsmall",
device="cuda",
lru_max_vram_gb=2.0,
)
Uses up to ~12Γ less VRAM than standard loading by streaming layers on demand.
Stream straight from the Hub (no disk)
import bigsmall
state_dict = bigsmall.stream_from_hub("wpferrell/qwen2.5-32b-instruct-bigsmall", device="cpu")
Decompresses directly from the HuggingFace CDN over HTTP range requests. With the default cache=False, no .bs file is ever written to disk (V10).
Decompress to safetensors
import bigsmall
from safetensors.torch import save_file
# bigsmall decompress works on local .bs files, not Hub repos, so
# stream the weights from the Hub and write them out as safetensors.
state_dict = bigsmall.stream_from_hub("wpferrell/qwen2.5-32b-instruct-bigsmall", device="cpu")
save_file(state_dict, "qwen2.5-32b-instruct-bigsmall.safetensors")
Original model
This is a lossless-compressed copy of Qwen/Qwen2.5-32B-Instruct. All credit to the original authors. The weights are unchanged.
Want to compress your own model?
pip install "bigsmall>=3.14.1"
bigsmall compress my-model/ -o my-model.bs
See github.com/wpferrell/Bigsmall for the full docs.
License
- Model weights: apache-2.0 β same as Qwen/Qwen2.5-32B-Instruct.
- BigSmall format: Elastic License 2.0 β free for personal, research, and commercial use.
- Commercial SaaS licensing: wpferrell@gmail.com
Citation
@misc{bigsmall2026,
title={BigSmall: Lossless Neural Network Weight Compression},
author={Ferrell, Will},
year={2026},
doi={10.5281/zenodo.20279247},
url={https://doi.org/10.5281/zenodo.20279247}
}
Requires
bigsmall >= 3.14.1 for the latest features. Earlier versions (>= 3.0.0) can still decode this model.
- Downloads last month
- 91
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support