Instructions to use NightBaRron1412/deepparse-r1-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NightBaRron1412/deepparse-r1-8b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-R1-Distill-Llama-8B") model = PeftModel.from_pretrained(base_model, "NightBaRron1412/deepparse-r1-8b") - Notebooks
- Google Colab
- Kaggle
File size: 598 Bytes
c9ca1eb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"train_file": "artifacts/training/train_paper.jsonl",
"output_dir": "artifacts/checkpoints/deepparse-r1-8b",
"model_name": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"epochs": 25,
"learning_rate": 0.0002,
"batch_size": 8,
"grad_accum": 4,
"lora_rank": 8,
"lora_alpha": 32,
"lora_dropout": 0.01,
"max_length": 512,
"bf16": false,
"attn_implementation": "eager",
"seed": 1337,
"eval_split": 0.0,
"save_steps": 200,
"log_steps": 25,
"target_modules": [
"q_proj",
"k_proj",
"v_proj",
"o_proj",
"gate_proj",
"up_proj",
"down_proj"
]
} |