Instructions to use Ponce-01/DFEP-03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Ponce-01/DFEP-03 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("Ponce-01/DFEP-03", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from Ponce-01/DFEP-03: direct link, hf CLI and curl.
- Browser
- Download file 632 Bytes
-
https://huggingface.co/Ponce-01/DFEP-03/resolve/main/adapter_config.json
- Command line
-
hf download hf://Ponce-01/DFEP-03/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/Ponce-01/DFEP-03/resolve/main/adapter_config.json
632 Bytes
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "abhishek/llama-2-7b-hf-small-shards", | |
| "bias": "none", | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.05, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 16, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "v_proj", | |
| "q_proj" | |
| ], | |
| "task_type": "CAUSAL_LM", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |