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