Instructions to use mamung/29b84e13-2f1c-406f-9e7e-fd35b6e5ff49 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/29b84e13-2f1c-406f-9e7e-fd35b6e5ff49 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") model = PeftModel.from_pretrained(base_model, "mamung/29b84e13-2f1c-406f-9e7e-fd35b6e5ff49") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 6, 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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"is_world_process_zero": true,
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"eval_samples_per_second": 11.667,
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}
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"logging_steps": 1,
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"eval_samples_per_second": 11.667,
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