Text Generation
PEFT
Safetensors
llama4_text
lora
sft
finance
devanagari
llama-4
conversational
4-bit precision
bitsandbytes
Instructions to use sidddd625/adaption_finance_local_devnagri_scrip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sidddd625/adaption_finance_local_devnagri_scrip with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit") model = PeftModel.from_pretrained(base_model, "sidddd625/adaption_finance_local_devnagri_scrip") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 479cd84469fe7df7508f0be6dfdbe49ed4caa15093b6212dc02c0cfe342a2dcc
- Size of remote file:
- 27.9 MB
- SHA256:
- 172c9eb4beafc72601690da3ccfcede5c2e6806a8d5ec1fca33e22acea8023a4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.