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consolidated-qwen-rank8
pratsinha/consolidated-qwen-rank8
consolidated-qwen-rank8 is a machine learning model from pratsinha. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
Consolidation + per-class LoRA compression of Qwen/Qwen1.5-0.5B. This artifact stores only the cheap learned tensors (7 shared per-class backbone matrices + per-layer rank-8 LoRA adapters + q/k/v biases). The frozen b…
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Updated Jun 14, 2026
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.pt66.9 MB · 100%
At a glance
- Library
- pytorch
- Access
- Public
- Created
- Jun 14, 2026
- Updated
- Jun 14, 2026
- SHA
- 0d7f94b2
Model card
From the Hugging Face model README
Consolidated Qwen1.5-0.5B (rank 8)
Consolidation + per-class LoRA compression of Qwen/Qwen1.5-0.5B. This artifact stores only
the cheap learned tensors (7 shared per-class backbone matrices + per-layer
rank-8 LoRA adapters + q/k/v biases). The frozen base model is pulled from
Qwen/Qwen1.5-0.5B at load time.
from hub import pull # from github.com/sinha-k-prat/consolidated-qwen
model, tok = pull("pratsinha/consolidated-qwen-rank8")
ids = tok("Weight consolidation works by", return_tensors="pt")
print(tok.decode(model.base.generate(**ids, max_new_tokens=60)[0]))
Research prototype — https://github.com/sinha-k-prat/consolidated-qwen
- Library
- pytorch
- Created
- Jun 14, 2026
- Updated
- Jun 14, 2026