Instructions to use imnbharath/IndicTransLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imnbharath/IndicTransLoRA with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="imnbharath/IndicTransLoRA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("imnbharath/IndicTransLoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
InLegalTrans LoRA Fine-tune
This model is a LoRA-based fine-tune of law-ai/InLegalTrans-En2Indic-1B, trained for legal domain translation from English to Indic languages.
Model Details
- Base Model: law-ai/InLegalTrans-En2Indic-1B
- Fine-tuning Method: LoRA (Low-Rank Adaptation)
- Domain: Legal
- Task: Translation (English → Indic)
Model tree for imnbharath/IndicTransLoRA
Base model
ai4bharat/indictrans2-en-indic-1B Finetuned
law-ai/InLegalTrans-En2Indic-1B