Text Generation
PEFT
Safetensors
quantum-computing
bitnet
lora
algorithm-recommendation
research-prototype
Instructions to use UlukaDev/qare-bitnet-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use UlukaDev/qare-bitnet-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/bitnet-b1.58-2B-4T-bf16") model = PeftModel.from_pretrained(base_model, "UlukaDev/qare-bitnet-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 838ea6744fc84f4a2ea03cdbeb24ab2ad79e8546f4ece7477392bf92f4957e85
- Size of remote file:
- 17.2 MB
- SHA256:
- 6b61860df92cd88daf79890eedb1ce4162a36cd1556ab3207dd5d69744974bb2
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