Instructions to use MHGanainy/16-clusters-imbalanced-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MHGanainy/16-clusters-imbalanced-9 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2-xl") model = PeftModel.from_pretrained(base_model, "MHGanainy/16-clusters-imbalanced-9") - Notebooks
- Google Colab
- Kaggle
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| "epoch": 1.0, | |
| "eval_steps": 500, | |
| "global_step": 148, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
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| "grad_norm": 0.17686977982521057, | |
| "learning_rate": 6.666666666666667e-06, | |
| "loss": 2.3132, | |
| "step": 100 | |
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| { | |
| "epoch": 1.0, | |
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| "train_runtime": 46.3579, | |
| "train_samples_per_second": 6.385, | |
| "train_steps_per_second": 3.193 | |
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| "logging_steps": 100, | |
| "max_steps": 148, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 1, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
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| "total_flos": 2689637233459200.0, | |
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| } | |