Instructions to use shibajustfor/26f86435-80d4-4b02-8a0b-3ac4a0a12e77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/26f86435-80d4-4b02-8a0b-3ac4a0a12e77 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Llama-2-13b-128k") model = PeftModel.from_pretrained(base_model, "shibajustfor/26f86435-80d4-4b02-8a0b-3ac4a0a12e77") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 50, 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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"logging_steps": 10,
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"eval_samples_per_second": 11.025,
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"learning_rate": 2.339555568810221e-05,
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