Instructions to use akacaptain/dragonclaw_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use akacaptain/dragonclaw_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "akacaptain/dragonclaw_model") - Notebooks
- Google Colab
- Kaggle
File size: 478 Bytes
956138b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"base_model": "meta-llama/Llama-3.2-3B-Instruct",
"dataset_path": "artifacts/training_data.jsonl",
"output_dir": "artifacts/model",
"lora_r": 16,
"lora_alpha": 32,
"lora_dropout": 0.05,
"backend": "hf-peft",
"dry_run": false,
"num_train_epochs": 1.0,
"per_device_train_batch_size": 2,
"gradient_accumulation_steps": 4,
"learning_rate": 0.0002,
"max_seq_length": 2048,
"warmup_ratio": 0.03,
"logging_steps": 10,
"save_steps": 200,
"seed": 42
} |