# Polpaca: The Polish Alpaca

Please find the model here: https://huggingface.co/mmosiolek/polpaca-lora-7b


This repository contains the polish translations of the datasets for constructing and evaluating instruction following models: Alpaca.


### Training
The following dataset was translated: https://github.com/gururise/AlpacaDataCleaned
It might be also found here: https://huggingface.co/datasets/yahma/alpaca-cleaned


For the translation process, I relied on GPT-3.5-Turbo and the free $18 credits granted by the OpenAI platform.
Unfortunately, the cost of the translation exceeded the amount granted, so I had to add $7 from my own pocket ;) 
Although the translation was extremely cheap, it took 5 days to complete.

The following prompt was used for the translation based on: https://arxiv.org/abs/2301.08745
```
Please provide the Polish translation for these sentences: [TEXT]
```

### Manual Quality Assessment
For evaluation the self-instruct (https://github.com/yizhongw/self-instruct) evaluation dataset was translated. 
This time with the help of DeepL that offers translation of 500K characters for free each month. 


Unfortunately this approach has certain limitations related to the fact, that some tasks from the original datasets can't be simply
translated to another language. For example we can't propagate ortographic errors from one language to another. 
It's necessary to keep it mind while manually reviewing the results.
language:pl license:cc-by-4.0 llama alpaca chat-gpt self-instruct gpt arxiv:2301.08745 region:us
{"language": ["pl"], "license": "cc-by-4.0", "tags": ["llama", "alpaca", "chat-gpt", "self-instruct", "gpt"]}
TAGS
#language-Polish #license-cc-by-4.0 #llama #alpaca #chat-gpt #self-instruct #gpt #arxiv-2301.08745 #region-us 

# Polpaca: The Polish Alpaca

Please find the model here: URL


This repository contains the polish translations of the datasets for constructing and evaluating instruction following models: Alpaca.


### Training
The following dataset was translated: URL
It might be also found here: URL


For the translation process, I relied on GPT-3.5-Turbo and the free $18 credits granted by the OpenAI platform.
Unfortunately, the cost of the translation exceeded the amount granted, so I had to add $7 from my own pocket ;) 
Although the translation was extremely cheap, it took 5 days to complete.

The following prompt was used for the translation based on: URL


### Manual Quality Assessment
For evaluation the self-instruct (URL evaluation dataset was translated. 
This time with the help of DeepL that offers translation of 500K characters for free each month. 


Unfortunately this approach has certain limitations related to the fact, that some tasks from the original datasets can't be simply
translated to another language. For example we can't propagate ortographic errors from one language to another. 
It's necessary to keep it mind while manually reviewing the results.
# Polpaca: The Polish Alpaca

Please find the model here: URL


This repository contains the polish translations of the datasets for constructing and evaluating instruction following models: Alpaca. ### Training
The following dataset was translated: URL
It might be also found here: URL


For the translation process, I relied on GPT-3.5-Turbo and the free $18 credits granted by the OpenAI platform.
Unfortunately, the cost of the translation exceeded the amount granted, so I had to add $7 from my own pocket ;) 
Although the translation was extremely cheap, it took 5 days to complete.

The following prompt was used for the translation based on: URL ### Manual Quality Assessment
For evaluation the self-instruct (URL evaluation dataset was translated. 
This time with the help of DeepL that offers translation of 500K characters for free each month. 


Unfortunately this approach has certain limitations related to the fact, that some tasks from the original datasets can't be simply
translated to another language. For example we can't propagate ortographic errors from one language to another. 
It's necessary to keep it mind while manually reviewing the results.
TAGS
#language-Polish #license-cc-by-4.0 #llama #alpaca #chat-gpt #self-instruct #gpt #arxiv-2301.08745 #region-us 
 # Polpaca: The Polish Alpaca

Please find the model here: URL


This repository contains the polish translations of the datasets for constructing and evaluating instruction following models: Alpaca. ### Training
The following dataset was translated: URL
It might be also found here: URL


For the translation process, I relied on GPT-3.5-Turbo and the free $18 credits granted by the OpenAI platform.
Unfortunately, the cost of the translation exceeded the amount granted, so I had to add $7 from my own pocket ;) 
Although the translation was extremely cheap, it took 5 days to complete.

The following prompt was used for the translation based on: URL ### Manual Quality Assessment
For evaluation the self-instruct (URL evaluation dataset was translated. 
This time with the help of DeepL that offers translation of 500K characters for free each month. 


Unfortunately this approach has certain limitations related to the fact, that some tasks from the original datasets can't be simply
translated to another language. For example we can't propagate ortographic errors from one language to another. 
It's necessary to keep it mind while manually reviewing the results.
passage: TAGS
#language-Polish #license-cc-by-4.0 #llama #alpaca #chat-gpt #self-instruct #gpt #arxiv-2301.08745 #region-us 
# Polpaca: The Polish Alpaca

Please find the model here: URL


This repository contains the polish translations of the datasets for constructing and evaluating instruction following models: Alpaca.### Training
The following dataset was translated: URL
It might be also found here: URL


For the translation process, I relied on GPT-3.5-Turbo and the free $18 credits granted by the OpenAI platform.
Unfortunately, the cost of the translation exceeded the amount granted, so I had to add $7 from my own pocket ;) 
Although the translation was extremely cheap, it took 5 days to complete.

The following prompt was used for the translation based on: URL### Manual Quality Assessment
For evaluation the self-instruct (URL evaluation dataset was translated. 
This time with the help of DeepL that offers translation of 500K characters for free each month. 


Unfortunately this approach has certain limitations related to the fact, that some tasks from the original datasets can't be simply
translated to another language. For example we can't propagate ortographic errors from one language to another. 
It's necessary to keep it mind while manually reviewing the results.