Instructions to use trangtrannnnn/b6c743d7-59d5-4102-b00e-c3c843a054ea with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/b6c743d7-59d5-4102-b00e-c3c843a054ea with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("samoline/0243b90c-8e39-4616-a4c6-82e4ad8a78c6") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/b6c743d7-59d5-4102-b00e-c3c843a054ea") - Notebooks
- Google Colab
- Kaggle
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "samoline/0243b90c-8e39-4616-a4c6-82e4ad8a78c6", | |
| "bias": "none", | |
| "fan_in_fan_out": null, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 16, | |
| "lora_dropout": 0.05, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 8, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "down_proj", | |
| "gate_proj", | |
| "o_proj", | |
| "up_proj" | |
| ], | |
| "task_type": "CAUSAL_LM", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |