Instructions to use VERSIL91/31c5e79c-6bf7-44bb-9f84-7d7fa7f6f608 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VERSIL91/31c5e79c-6bf7-44bb-9f84-7d7fa7f6f608 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "VERSIL91/31c5e79c-6bf7-44bb-9f84-7d7fa7f6f608") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 5, checkpoint
Browse files
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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"is_world_process_zero": true,
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"eval_samples_per_second": 213.909,
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"eval_steps_per_second": 107.402,
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"step": 4
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"logging_steps": 1,
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"epoch": 0.0353356890459364,
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"eval_steps": 2,
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"global_step": 5,
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"is_hyper_param_search": false,
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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": 213.909,
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"eval_steps_per_second": 107.402,
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"step": 4
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{
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"learning_rate": 5e-05,
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"should_evaluate": false,
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"should_save": true,
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"should_training_stop": true
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"attributes": {}
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"total_flos": 3631153152.0,
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"train_batch_size": 2,
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"trial_name": null,
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