Instructions to use 0xlexor/genesys with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0xlexor/genesys with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "0xlexor/genesys") - Notebooks
- Google Colab
- Kaggle
| { | |
| "lora_name": "surge_final", | |
| "always_override": false, | |
| "q_proj_en": true, | |
| "v_proj_en": true, | |
| "k_proj_en": false, | |
| "o_proj_en": false, | |
| "gate_proj_en": false, | |
| "down_proj_en": false, | |
| "up_proj_en": false, | |
| "save_steps": 10000, | |
| "micro_batch_size": 6, | |
| "batch_size": 500, | |
| "epochs": 3, | |
| "learning_rate": "3e-4", | |
| "lr_scheduler_type": "linear", | |
| "lora_rank": 512, | |
| "lora_alpha": 1024, | |
| "lora_dropout": 0.05, | |
| "cutoff_len": 256, | |
| "dataset": "dataset", | |
| "eval_dataset": "None", | |
| "format": "alpaca-format", | |
| "eval_steps": 100, | |
| "raw_text_file": "None", | |
| "overlap_len": 128, | |
| "newline_favor_len": 128, | |
| "higher_rank_limit": false, | |
| "warmup_steps": 100, | |
| "optimizer": "adamw_torch", | |
| "hard_cut_string": "\\n\\n\\n", | |
| "train_only_after": "", | |
| "stop_at_loss": 0, | |
| "add_eos_token": false, | |
| "min_chars": 0, | |
| "report_to": "None" | |
| } |