Instructions to use xju-arlab/vbench-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use xju-arlab/vbench-model with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download multiple_objects/training_config.json from xju-arlab/vbench-model: direct link, hf CLI and curl.
- Browser
- Download file 1.11 kB
-
https://huggingface.co/xju-arlab/vbench-model/resolve/main/multiple_objects/training_config.json
- Command line
-
hf download hf://xju-arlab/vbench-model/multiple_objects/training_config.json
-
curl -L -o training_config.json https://huggingface.co/xju-arlab/vbench-model/resolve/main/multiple_objects/training_config.json
1.11 kB
| { | |
| "task": "objects", | |
| "model_name_or_path": "/data1/wenbiao_zhao/models/Qwen3-8B", | |
| "train_jsonl": "data/formal/v6/objects/train.jsonl", | |
| "output_dir": "runs/formal/v6-8b/objects", | |
| "eval_jsonl": "data/formal/v6/objects/dev.jsonl", | |
| "model_revision": "b968826d9c46dd6066d109eabc6255188de91218", | |
| "tokenizer_name_or_path": null, | |
| "max_steps": 900, | |
| "max_length": 2048, | |
| "per_device_train_batch_size": 1, | |
| "gradient_accumulation_steps": 4, | |
| "learning_rate": 0.0001, | |
| "lr_scheduler_type": "cosine", | |
| "warmup_steps": 10, | |
| "lora_r": 16, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.0, | |
| "lora_target_modules": "all-linear", | |
| "seed": 20260919, | |
| "bf16": true, | |
| "fp16": false, | |
| "gradient_checkpointing": true, | |
| "logging_steps": 10, | |
| "save_steps": 150, | |
| "save_total_limit": 3, | |
| "packing": false, | |
| "completion_only_loss": true, | |
| "local_files_only": true, | |
| "allow_download": false, | |
| "max_samples": null, | |
| "eval_fraction": 0.0, | |
| "dev_exact_match_every": 150, | |
| "dev_exact_match_samples": 24, | |
| "dev_exact_match_max_new_tokens": 96, | |
| "report_to": "none", | |
| "dataset_num_proc": 1, | |
| "extra": {} | |
| } | |