---
language:
- ur
license: apache-2.0
library_name: peft
base_model: mistralai/Mistral-7B-Instruct-v0.3
tags:
- lora
- qlora
- education
- k12
- indian-languages
- cbse
- ncert
- bharatllm
- foundryailabs
datasets:
- FoundryAILabs/k12-indian-curriculum-4.9m
pipeline_tag: text-generation
---

# BharatLLM Urdu -- K-12 Education LoRA

A **QLoRA adapter** for Mistral-7B, fine-tuned on **CBSE/NCERT K-12 curriculum** data in **Urdu** (اردو).

Part of the **BharatLLM** project: 13 LoRA adapters (12 K-12 languages + 1 BTech Engineering).

## Model Details

| Property | Value |
|----------|-------|
| **Base Model** | mistralai/Mistral-7B-Instruct-v0.3 |
| **Method** | QLoRA (4-bit quantization + LoRA, r=64) |
| **Trainable Parameters** | 167,772,160 (2.26% of 7.4B) |
| **Training Library** | Unsloth |
| **Language** | Urdu (اردو) |
| **Domain** | K-12 Education (CBSE/NCERT, Grades 6-12) |
| **Training Data** | ~374K curriculum-aligned Q&A pairs |
| **License** | Apache 2.0 |

## Quick Start (Unsloth -- Fastest)

```python
from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="FoundryAILabs/bharat-urdu-7b-lora",
    max_seq_length=2048,
    load_in_4bit=True,
)
FastLanguageModel.for_inference(model)

inputs = tokenizer("[INST] What is photosynthesis? [/INST]", return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Using with HuggingFace Transformers

```python
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3", load_in_4bit=True, device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
model = PeftModel.from_pretrained(base, "FoundryAILabs/bharat-urdu-7b-lora")
```

## All BharatLLM Models

| Model | Language | Type |
|-------|----------|------|
| [FoundryAILabs/bharat-english-7b-lora](https://huggingface.co/FoundryAILabs/bharat-english-7b-lora) | English | K-12 |
| [FoundryAILabs/bharat-hindi-7b-lora](https://huggingface.co/FoundryAILabs/bharat-hindi-7b-lora) | Hindi | K-12 |
| [FoundryAILabs/bharat-bengali-7b-lora](https://huggingface.co/FoundryAILabs/bharat-bengali-7b-lora) | Bengali | K-12 |
| [FoundryAILabs/bharat-telugu-7b-lora](https://huggingface.co/FoundryAILabs/bharat-telugu-7b-lora) | Telugu | K-12 |
| [FoundryAILabs/bharat-tamil-7b-lora](https://huggingface.co/FoundryAILabs/bharat-tamil-7b-lora) | Tamil | K-12 |
| [FoundryAILabs/bharat-kannada-7b-lora](https://huggingface.co/FoundryAILabs/bharat-kannada-7b-lora) | Kannada | K-12 |
| [FoundryAILabs/bharat-malayalam-7b-lora](https://huggingface.co/FoundryAILabs/bharat-malayalam-7b-lora) | Malayalam | K-12 |
| [FoundryAILabs/bharat-marathi-7b-lora](https://huggingface.co/FoundryAILabs/bharat-marathi-7b-lora) | Marathi | K-12 |
| [FoundryAILabs/bharat-gujarati-7b-lora](https://huggingface.co/FoundryAILabs/bharat-gujarati-7b-lora) | Gujarati | K-12 |
| [FoundryAILabs/bharat-odia-7b-lora](https://huggingface.co/FoundryAILabs/bharat-odia-7b-lora) | Odia | K-12 |
| [FoundryAILabs/bharat-punjabi-7b-lora](https://huggingface.co/FoundryAILabs/bharat-punjabi-7b-lora) | Punjabi | K-12 |
| [FoundryAILabs/bharat-urdu-7b-lora](https://huggingface.co/FoundryAILabs/bharat-urdu-7b-lora) | Urdu | K-12 |
| [FoundryAILabs/bharat-btech-7b-lora](https://huggingface.co/FoundryAILabs/bharat-btech-7b-lora) | English | BTech Engineering |

**Website**: [foundryailabs.io](https://foundryailabs.io) | **GitHub**: [github.com/foundryailabs/BharatLLM](https://github.com/foundryailabs/BharatLLM)