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README.md
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---
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license: apache-2.0
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language:
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- en
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- hi
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metrics:
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- perplexity
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base_model: meta-llama/Llama-2-7b-hf
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- code
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datasets:
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- zicsx/mC4-Hindi-Cleaned-3.0
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---
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![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
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# QuantFactory/Llama2-7B-Hindi-finetuned-GGUF
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This is quantized version of [subhrokomol/Llama2-7B-Hindi-finetuned](https://huggingface.co/subhrokomol/Llama2-7B-Hindi-finetuned) created using llama.cpp
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# Original Model Card
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# Finetune Llama-2-7B-hf on Hindi dataset after transtokenization
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This model was trained on 24GB of RTX A500 on zicsx/mC4-Hindi-Cleaned-3.0 dataset (1%) for 3 hours.
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We used Hugging Face PEFT-LoRA PyTorch for training.
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Transtokenization process in --
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