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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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base_model: NousResearch/Meta-Llama-3.1-8B-Instruct
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library_name: peft
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tags:
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- llama-factory
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- lora
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datasets:
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- Nekochu/Luminia-mixture
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language:
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- en
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---
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- Fine-tuning of ‘Llama-3.1-8B’ with a focus on RP and uncensored.
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<details>
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<summary>This training can be replicated using LLaMA-Factory. </summary>
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Stage A: Continued **S**upervised **F**ine-**T**uning, QA
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```
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set CUDA_VISIBLE_DEVICES=0 && llamafactory-cli train --stage sft --do_train True --model_name_or_path NousResearch/Meta-Llama-3.1-8B-Instruct --preprocessing_num_workers 1 --finetuning_type lora --template alpaca --rope_scaling linear --flash_attn fa2 --dataset_dir data --dataset faproulette_co-OCR-fix-gpt4o_qa,ascii_art,Uncensored_DAN,Lumimaid-v2,Degrees_of_Lewdity --cutoff_len 8192 --learning_rate 5e-05 --num_train_epochs 1.0 --max_samples 100000 --per_device_train_batch_size 1 --gradient_accumulation_steps 1 --lr_scheduler_type cosine --max_grad_norm 1.0 --logging_steps 10 --save_steps 1000 --warmup_steps 1000 --neftune_noise_alpha 5 --optim adamw_8bit --packing True --neat_packing True --report_to none --output_dir saves\LLaMA3.1-8B-Chat\lora\Luminia-8B-RP --bf16 True --plot_loss True --ddp_timeout 180000000 --include_num_input_tokens_seen True --quantization_bit 4 --quantization_method bitsandbytes --lora_rank 32 --lora_alpha 64 --lora_dropout 0.15 --create_new_adapter True --lora_target all --use_adam_mini True
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```
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<details>
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<summary>dataset_info.json</summary>
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`dataset_info.json`:
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```json
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...
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```
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</details>
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</details>
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