Instructions to use OpenSportsLab/OSL-VQA-XFOUL-XVARS-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OpenSportsLab/OSL-VQA-XFOUL-XVARS-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("base_model_videoChatGPT") model = PeftModel.from_pretrained(base_model, "OpenSportsLab/OSL-VQA-XFOUL-XVARS-lora") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "xvars_videochatgpt_lora", | |
| "model_id": "/home/vorajv/X-VARS/weights/base_model_videoChatGPT", | |
| "status": "trained", | |
| "multimodal_training": true, | |
| "video_token_len": 300, | |
| "lora_target_modules": [ | |
| "mm_projector", | |
| "upsample_features", | |
| "up_proj", | |
| "down_proj", | |
| "gate_proj", | |
| "k_proj", | |
| "q_proj", | |
| "v_proj", | |
| "o_proj" | |
| ], | |
| "num_train_samples": 16568, | |
| "num_valid_samples": 2219, | |
| "generated_validation_accepted": true, | |
| "generated_validation_history": "/home/vorajv/opensportslib/checkpoints_vqa_lora/model/860f3cef/xvars_videochatgpt_lora/generated_validation.json", | |
| "best_generated_checkpoint": "/home/vorajv/opensportslib/checkpoints_vqa_lora/model/860f3cef/xvars_videochatgpt_lora/generated_validation_best" | |
| } |