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README.md
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---
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license: llama2
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language:
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- hu
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- en
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tags:
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- puli
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- llama
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- finetuned
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base_model: ariel-ml/PULI-LlumiX-32K-instruct-f16-0.2
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pipeline_tag: text-generation
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---
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# PULI LlumiX 32K instruct (6.74B billion parameter)
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<img src="logo.webp" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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Intruct finetuned version of NYTK/PULI-LlumiX-32K.
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## Provided files
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| Quant method | Bits | Use case |
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| ---- | ---- | ---- |
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| Q3_K_M | 3 | very small, high quality loss |
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| Q4_K_S | 4 | small, greater quality loss |
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| Q4_K_M | 4 | medium, balanced quality - recommended |
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| Q5_K_S | 5 | large, low quality loss - recommended |
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| Q5_K_M | 5 | large, very low quality loss - recommended |
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| Q6_K | 6 | very large, extremely low quality loss |
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| Q8_0 | 8 | very large, extremely low quality loss - not recommended |
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## Training platform
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[Runpod](https://runpod.ui) RTX 4090 GPU
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## Hyper parameters
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- Epoch: 3
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- LoRA rank (r): 16
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- LoRA alpha: 16
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- Lr: 2e-4
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- Lr scheduler: cosine
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- Optimizer: adamw_8bit
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- Weight decay: 0.01
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## Dataset
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boapps/szurkemarha
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Only Hungarian instructions were selected: ~53000 prompts.
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## Prompt format: ChatML
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```
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<|im_start|>system
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Egy segítőkész mesterséges intelligencia asszisztens vagy. Válaszold meg a kérdést legjobb tudásod szerint!<|im_end|>
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<|im_start|>user
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Ki a legerősebb szuperhős?<|im_end|>
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<|im_start|>assistant
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A legerősebb szuperhős a Marvel univerzumában Hulk.<|im_end|>
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```
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## Base model
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- Trained with OpenChatKit [github](https://github.com/togethercomputer/OpenChatKit)
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- The [LLaMA-2-7B-32K](https://huggingface.co/togethercomputer/LLaMA-2-7B-32K) model were continuously pretrained on Hungarian dataset
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- The model has been extended to a context length of 32K with position interpolation
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- Checkpoint: 100 000 steps
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## Base model dataset for continued pretraining
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- Hungarian: 7.9 billion words, documents (763K) that exceed 5000 words in length
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- English: Long Context QA (2 billion words), BookSum (78 million words)
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## Limitations
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- max_seq_length = 32 768
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- float16
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- vocab size: 32 000
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