Instructions to use aiden200/anon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aiden200/anon with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmms-lab/llava-onevision-qwen2-7b-ov") model = PeftModel.from_pretrained(base_model, "aiden200/anon") - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from aiden200/anon: direct link, hf CLI and curl.
- Browser
- Download file 620 Bytes
-
https://huggingface.co/aiden200/anon/resolve/20299bbc20dd41663b03cb0f8164410b28b8da0c/adapter_config.json
- Command line
-
hf download hf://aiden200/anon@20299bbc20dd41663b03cb0f8164410b28b8da0c/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/aiden200/anon/resolve/20299bbc20dd41663b03cb0f8164410b28b8da0c/adapter_config.json
620 Bytes
| { | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "lmms-lab/llava-onevision-qwen2-7b-ov", | |
| "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": [ | |
| "connector", | |
| "mm_projector", | |
| "response_head", | |
| "lm_head", | |
| "informative_head", | |
| "relevance_head", | |
| "uncertainty_head" | |
| ], | |
| "peft_type": "LORA", | |
| "r": 8, | |
| "revision": null, | |
| "target_modules": "model\\.layers.*(q_proj|k_proj|v_proj|gate_proj)$", | |
| "task_type": "CAUSAL_LM" | |
| } |