README.md

---

license: apache-2.0
language:
- en
- hi
metrics:
- perplexity
base_model: meta-llama/Llama-2-7b-hf
pipeline_tag: text-generation
library_name: transformers
tags:
- code
datasets:
- zicsx/mC4-Hindi-Cleaned-3.0

---

![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)

# QuantFactory/Llama2-7B-Hindi-finetuned-GGUF
This is quantized version of [subhrokomol/Llama2-7B-Hindi-finetuned](https://huggingface.co/subhrokomol/Llama2-7B-Hindi-finetuned) created using llama.cpp

# Original Model Card



# Finetune Llama-2-7B-hf on Hindi dataset after transtokenization
This model was trained on 24GB of RTX A500 on zicsx/mC4-Hindi-Cleaned-3.0 dataset (1%) for 3 hours.

We used Hugging Face PEFT-LoRA PyTorch for training.

Transtokenization process in  --