Instructions to use SKT27182/Flan_T5_Instruct_Fine_Tuning_QLoRA_Dataset_Open_Orca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SKT27182/Flan_T5_Instruct_Fine_Tuning_QLoRA_Dataset_Open_Orca with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large") model = PeftModel.from_pretrained(base_model, "SKT27182/Flan_T5_Instruct_Fine_Tuning_QLoRA_Dataset_Open_Orca") - Notebooks
- Google Colab
- Kaggle
Commit History
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NumExample_75000Finetune_Epoch_6
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NumExample_75000Finetune_Epoch_5
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NumExample_75000Finetune_Epoch_4
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NumExample_75000Finetune_Epoch_3
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NumExample_75000Finetune_Epoch_3
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NumExample_75000Finetune_Epoch_3
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Final Fine Tuned LoRA layer with SKT27182/flan_t5_large_fine_tuned_head as a base model
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Final Fine Tuned LoRA layer with SKT27182/flan_t5_large_fine_tuned_head as a base model
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NumExample_75000Finetune_Epoch_3
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NumExample_75000Finetune_Epoch_2
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NumExample_75000Finetune_Epoch_1
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trying to save model's head along with lora layer
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Fine tuning on first 10k dataset for 5 epochs, made the model's head as Trainable
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Fine Tune on first set of 10k dataset, epoch 5
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Fine Tune on first set of 10k dataset, epoch 5
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Fine Tune on first set of 10k dataset, epoch 5
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Fine Tune on first set of 10k dataset, epoch 5
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Fine Tune on first set of 10k dataset, epoch 5
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First Fine Tune on 30k dataset
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Test Commit
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Training in progress, step 250
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initial commit
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