Instructions to use aleegis12/3ee9f7bb-abd2-40ce-bf06-792a5f44f0fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis12/3ee9f7bb-abd2-40ce-bf06-792a5f44f0fa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("beomi/polyglot-ko-12.8b-safetensors") model = PeftModel.from_pretrained(base_model, "aleegis12/3ee9f7bb-abd2-40ce-bf06-792a5f44f0fa") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 450, 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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{
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"epoch":
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"global_step":
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"eval_samples_per_second": 10.707,
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"eval_steps_per_second": 2.717,
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"step": 300
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}
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"logging_steps": 50,
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"early_stopping_threshold": 0.0
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"TrainerControl": {
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"global_step": 450,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"eval_samples_per_second": 10.707,
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"TrainerControl": {
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