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
| { | |
| "data_dir": "dataset", | |
| "out": "/content/drive/MyDrive/qare-lora-v3", | |
| "model": "microsoft/bitnet-b1.58-2B-4T-bf16", | |
| "epochs": 3.0, | |
| "bs": 8, | |
| "grad_accum": 2, | |
| "lr": 0.0001, | |
| "maxlen": 768, | |
| "lora_r": 16, | |
| "lora_alpha": 32, | |
| "max_steps": -1, | |
| "full_ft": false | |
| } |