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hiyasvyas/ortho-vision-qlora-final-v4
ortho-vision-qlora-final-v4 is a machine learning model from hiyasvyas. 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 peft. The card lists the license as mit.
Final v4 LoRA adapter for orthographic projection behavior.
Downloads · 30 days
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9% of all-time downloads
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.safetensors329 MB · 97%
From the Hugging Face model README
Final v4 LoRA adapter for orthographic projection behavior.
Given an image of a unit-cube solid (unit grid + marked FRONT edge), the model outputs:
dims: ZxYxX
top:
...
front:
...
right:
...
unsloth/Qwen2.5-VL-3B-Instruct (4-bit QLoRA / Unsloth)
hiyasvyas/orthographic-views-vision-final-v4
| Setting | Value |
|---|---|
| Method | QLoRA (Unsloth) |
| LoRA rank | 32 |
| LR | 2e-4 |
| Epochs | 2 |
| Batch | 2 × grad_accum 4 |
| Metric | TUNED (final v4) |
|---|---|
| format_ok | 98% |
| dims_ok | 88% |
| top_ok | 41% |
| front_ok | 51% |
| right_ok | 49% |
| exact | 23% |
Base model exact ≈ 0% on the same set (prompt litmus fails). Exact wins byte-identical to gold; train/golden label leakage 2/100.
from unsloth import FastVisionModel
model, tokenizer = FastVisionModel.from_pretrained(
"hiyasvyas/ortho-vision-qlora-final-v4", # or load base then attach adapter
load_in_4bit=True,
)
# If this repo is adapter-only, load base then:
# model.load_adapter("hiyasvyas/ortho-vision-qlora-final-v4")
Given an image of a unit-cube solid (grid + FRONT edge), output
dims: ZxYxXthen exactly three ASCII gridstop:/front:/right:(third-angle), only./#, sizes matching dims.