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
File size: 278 Bytes
8a46533 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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
} |