Instructions to use VextLabsinc/gem-ruby with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VextLabsinc/gem-ruby with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("VextLabsinc/juwel-beryl") model = PeftModel.from_pretrained(base_model, "VextLabsinc/gem-ruby") - Notebooks
- Google Colab
- Kaggle
File size: 809 Bytes
0f2cbc5 93ff07d 43157f9 0f2cbc5 93ff07d 0f2cbc5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | NOTICE — JUWEL GEM open-weight adapter (code)
Copyright 2026 Vext Labs, Inc.
This is a LoRA adapter for the JUWEL base line (JUWEL Beryl, 80-layer),
which is derived from Qwen3-VL-32B-Instruct by Alibaba Cloud (Tongyi Qianwen Lab),
released under the Apache License 2.0. Original base model:
https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct
Modifications by Vext Labs, Inc.: refusal-direction abliteration, CIP organic
upscale (additional transformer layers, trained), and this domain LoRA adapter.
Attribution only — the "Qwen"/"Alibaba" names and marks are used solely to satisfy
Apache-2.0 attribution and do NOT imply endorsement by Alibaba Cloud.
Apache-2.0 requires retaining this NOTICE and the LICENSE file in redistributions,
and stating that changes were made (they were — see above).
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