Video-Text-to-Text
PEFT
llava
video-understanding
long-video
visual-question-answering
lora
qwen2
cvpr2026
Instructions to use Fujitsu/QViC-MF-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Fujitsu/QViC-MF-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmms-lab/LLaVA-Video-7B-Qwen2") model = PeftModel.from_pretrained(base_model, "Fujitsu/QViC-MF-7B") - Notebooks
- Google Colab
- Kaggle
File size: 535 Bytes
f4b52a8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"auto_mapping": null,
"base_model_name_or_path": "lmms-lab/LLaVA-Video-7B-Qwen2",
"bias": "none",
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": true,
"layers_pattern": null,
"layers_to_transform": null,
"lora_alpha": 16,
"lora_dropout": 0.05,
"modules_to_save": null,
"peft_type": "LORA",
"r": 64,
"revision": null,
"target_modules": "encoder\\.model\\.layers\\.\\d+\\.(mlp\\.(up_proj|gate_proj|down_proj)|self_attn\\.(q_proj|v_proj|k_proj|o_proj))",
"task_type": "CAUSAL_LM"
} |