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README.md
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---
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license: apache-2.0
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datasets:
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- cerebras/SlimPajama-627B
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- bigcode/starcoderdata
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- OpenAssistant/oasst_top1_2023-08-25
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language:
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- en
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---
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<div align="center">
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# TinyLlama-1.1B
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</div>
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https://github.com/jzhang38/TinyLlama
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The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. The training has started on 2023-09-01.
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<div align="center">
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<img src="./TinyLlama_logo.png" width="300"/>
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</div>
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We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.
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#### This Model
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This is the chat model finetuned on [PY007/TinyLlama-1.1B-intermediate-step-240k-503b](https://huggingface.co/PY007/TinyLlama-1.1B-intermediate-step-240k-503b). The dataset used is [OpenAssistant/oasst_top1_2023-08-25](https://huggingface.co/datasets/OpenAssistant/oasst_top1_2023-08-25).
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**Update from V0.1: 1. Different dataset. 2. Different chat format (now [chatml](https://github.com/openai/openai-python/blob/main/chatml.md) formatted conversations).**
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