Instructions to use BEncoderRT/Pythia-QLoRA-Instruction-Tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BEncoderRT/Pythia-QLoRA-Instruction-Tuning with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("EleutherAI/pythia-1B-deduped") model = PeftModel.from_pretrained(base_model, "BEncoderRT/Pythia-QLoRA-Instruction-Tuning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbc7006a810212b53de26c5bc2e4fb0913b4e42892779d27565a1e12d10db72f
- Size of remote file:
- 16.8 MB
- SHA256:
- 1f70c7c3f33acab31de58a12f78d12e07f1e61b40b4d07728f484a432e7776cb
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