AI is happening. The future is updating.TinyLlama-1.1B-Chat-v0.6
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 ππ. The training has started on 2023-09-01. 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. This is the chat model finetuned on top of TinyLlama/TinyLlama-1.1B-intermediate-step-955k-2T. **We follow HF's Zephyr's training recipe.** The model was " initially fine-tuned on a variant of the `UltraChat` dataset, which contains a diverse range of synthetic dialogues generated by ChatGPT. We then further aligned the model with π€ TRL's `DPOTrainer` on the openbmb/UltraFeedback dataset, which contain 64k prompts and model completions that are ranked by GPT-4."
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 ππ. The training has started on 2023-09-01. 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. This is the chat model finetuned on top of TinyLlama/TinyLlama-1.1B-intermediate-step-955k-2T. **We follow HF's Zephyr's training recipe.** The model was " initially fine-tuned on a variant of the `UltraChat` dataset, which contains a diverse range of synthetic dialogues generated by ChatGPT. We then further aligned the model with π€ TRL's `DPOTrainer` on the openbmb/UltraFeedback dataset, which contain 64k prompts and model completions that are ranked by GPT-4."