Correct LoRA rank in card: r=64, alpha=128 (was a fleet-wide r=64 assumption)
Browse files
README.md
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@@ -31,7 +31,7 @@ Never claim first/all weights / AGI / never-forgets / cheapest-ever.
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## Base model
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- **Required base:** `VextLabsinc/juwel-beryl`
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- **Architecture notes:** Base = JUWEL Beryl (80-layer, hidden 5120, 64 heads, intermediate 25600; internal lineage theron-base-v9 + one CIP rung). This PEFT LoRA is **native to that 80-layer geometry** (`layers_to_transform` 0-79, r=64) — it is not padded and not drop-in on any other JUWEL base. Base architecture is `Qwen3VLForConditionalGeneration` (image-text-to-text), so load it with `AutoModelForImageTextToText`, not `AutoModelForCausalLM`.
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- **Base license / attribution:** see `NOTICE`
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If this is a **LoRA / PEFT adapter**, load base first, then:
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## Base model
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- **Required base:** `VextLabsinc/juwel-beryl`
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+
- **Architecture notes:** Base = JUWEL Beryl (80-layer, hidden 5120, 64 heads, intermediate 25600; internal lineage theron-base-v9 + one CIP rung). This PEFT LoRA is **native to that 80-layer geometry** (`layers_to_transform` 0-79, r=64, alpha=128) — it is not padded and not drop-in on any other JUWEL base. Base architecture is `Qwen3VLForConditionalGeneration` (image-text-to-text), so load it with `AutoModelForImageTextToText`, not `AutoModelForCausalLM`.
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- **Base license / attribution:** see `NOTICE`
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If this is a **LoRA / PEFT adapter**, load base first, then:
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