Text Generation
PEFT
Safetensors
lora
qlora
invoice-extraction
information-extraction
qwen2.5
ocr
conversational
Instructions to use trishpurkait/billstructai-qwen-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trishpurkait/billstructai-qwen-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "trishpurkait/billstructai-qwen-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 696579596c36af21376c99dadb6dc61a2019797c8ba2c4ce543146517c40789b
- Size of remote file:
- 73.9 MB
- SHA256:
- 6039b7f79e316fa95ba396113292b237d8e6d3716234bb0c817852314727c5f0
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