Instructions to use gulaschnascher4000/lora_0-5_3B-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gulaschnascher4000/lora_0-5_3B-instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "gulaschnascher4000/lora_0-5_3B-instruct") - Notebooks
- Google Colab
- Kaggle
lora_0-5_3B-instruct / runs /Jan16_18-03-50_pss5xry2f0aq /events.out.tfevents.1737050783.pss5xry2f0aq.165850.0
- Xet hash:
- b6d5998f3a3bca2180474e6f2e110e0f89f3151299488f81d74aea35ea6611b4
- Size of remote file:
- 16.2 kB
- SHA256:
- b7ac0bc769328b2584fd7037922c1f54bf683b6015de0aca2aeb0c44fb81025a
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