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
File size: 605 Bytes
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license: apache-2.0
base_model: law-ai/InLegalTrans-En2Indic-1B
tags:
- legal
- translation
- lora
- indic
- fine-tuned
language:
- en
library_name: transformers
---
# InLegalTrans LoRA Fine-tune
This model is a LoRA-based fine-tune of [law-ai/InLegalTrans-En2Indic-1B](https://huggingface.co/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)
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