Instructions to use dimasik87/72c2c260-2713-4915-922b-1925fe806e3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/72c2c260-2713-4915-922b-1925fe806e3d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0") model = PeftModel.from_pretrained(base_model, "dimasik87/72c2c260-2713-4915-922b-1925fe806e3d") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 20, 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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"best_metric": 1.
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"best_model_checkpoint": "miner_id_24/checkpoint-
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"epoch": 0.
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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": 15.441,
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"eval_steps_per_second": 7.732,
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"step": 10
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}
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"logging_steps": 3,
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"eval_samples_per_second": 15.441,
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"step": 20
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