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| Category | v0 Checkpoint | Global LoRA (Round 10) | Training Version |
|---|---|---|---|
| Entertainment | ✅ checkpoint-387 | ✅ global_lora_10 | v0-20260131-213955 |
| Lives | ✅ checkpoint-500 | ✅ global_lora_10 | v0-20260201-080741 |
| Office | ✅ checkpoint-1000 | ✅ global_lora_10 | v0-20260131-211441 |
| Shopping | ✅ checkpoint-1000 | ✅ global_lora_10 | v0-20260201-062221 |
| Traveling | ✅ checkpoint-500 | ✅ global_lora_10 | v0-20260131-211143 |
qwen2vl-7b-lora-categories/
├── Entertainment/
│ ├── v0/ # Initial checkpoint LoRA
│ └── global_lora_10/ # Round 10 federated LoRA
├── Lives/
│ ├── v0/
│ └── global_lora_10/
├── Office/
│ ├── v0/
│ └── global_lora_10/
├── Shopping/
│ ├── v0/
│ └── global_lora_10/
└── Traveling/
├── v0/
└── global_lora_10/1from peft import PeftModel
2from transformers import Qwen2VLForConditionalGeneration
3
4# Load base model
5base_model = Qwen2VLForConditionalGeneration.from_pretrained(
6 "Qwen/Qwen2-VL-7B-Instruct",
7 torch_dtype="auto",
8 device_map="auto"
9)
10
11# Load a specific category LoRA (e.g., Entertainment global_lora_10)
12model = PeftModel.from_pretrained(
13 base_model,
14 "bmh201708/qwen2vl-7b-lora-categories",
15 subfolder="Entertainment/global_lora_10"
16)1from huggingface_hub import snapshot_download
2
3# Download specific category LoRA
4local_path = snapshot_download(
5 repo_id="bmh201708/qwen2vl-7b-lora-categories",
6 allow_patterns=["Entertainment/global_lora_10/*"]
7)