Instructions to use Fawazzx/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Fawazzx/outputs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Fawazzx/Saul-Instruct-v1_sharded") model = PeftModel.from_pretrained(base_model, "Fawazzx/outputs") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 5
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- training_steps:
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- mixed_precision_training: Native AMP
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### Training results
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 5
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- training_steps: 100
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- mixed_precision_training: Native AMP
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### Training results
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runs/May08_07-21-21_269ee2e04412/events.out.tfevents.1715153117.269ee2e04412.302.0
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version https://git-lfs.github.com/spec/v1
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size 26175
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training_args.bin
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size 4984
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version https://git-lfs.github.com/spec/v1
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