Instructions to use shibajustfor/97e6c917-e820-40ce-af2e-b33a1b676b69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/97e6c917-e820-40ce-af2e-b33a1b676b69 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1_5") model = PeftModel.from_pretrained(base_model, "shibajustfor/97e6c917-e820-40ce-af2e-b33a1b676b69") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 39, checkpoint
Browse files
last-checkpoint/adapter_model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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"logging_steps": 10,
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"loss": 1.7184,
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{
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"eval_loss": 1.7781810760498047,
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"eval_samples_per_second": 62.753,
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"eval_steps_per_second": 31.377,
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"step": 39
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"logging_steps": 10,
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