🚨 T-lite is designed for further fine-tuning and is not intended as a ready-to-use conversational assistant. Users are advised to exercise caution and are responsible for any additional training and oversight required to ensure the model's responses meet acceptable ethical and safety standards. The responsibility for incorporating this model into industrial or commercial solutions lies entirely with those who choose to deploy it.
Description
T-lite-instruct-0.1 is an instruct version of the T-lite-0.1 model.
T-lite-instruct-0.1 was trained in bf16.
📚 Dataset
Contexts
For the instruction dataset, the contexts are obtained from:
Open Source English-language datasets (such as UltraFeedback, HelpSteer, SHP, and so on)
Translations of English-language datasets through machine translation
Synthetic grounded QA contexts, generated from pre-training datasets
The translated contexts are filtered using classifiers.
SFT
The responses to the contexts are generated by a strong model and the training is exclusively carried out on these responses. This avoids training the model on poor-quality translations.
We used Russian version of Arena benchmark from Vikhrmodels and Arena Hard Auto codebase
for evaluation. As baseline model we chose gpt3.5-turbo-0125 and the judge was gpt-4-1106-preview.
Конечно, вот рецепт для вкусной домашней пиццы, который можно адаптировать под разные вкусы и предпочтения. Важно, чтобы тесто было мягким и воздушным, а начинка — сочной и ароматной.
### Ингредиенты для теста:
- 500 г муки (лучше использовать смесь пшеничной и цельнозерновой)
- 1 ч. л. сухих дрожжей (или 7 г свежих)
- 1 ч. л. сахара
- 1 ч. л. соли
- 1 ст. л. оливкового масла
- 300 мл тёплой воды
- 1 яйцо (для смазки)
### Ингредиенты для начинки (примерный набор):
- 200 г томатного соуса (можно сделать самому из свежих помидоров или использовать готовый)
- 200 г моцареллы, нарезанной ломтиками
- 100 г сыра пармезан (тертый)
- 100 г ветчины или колбасы
- 100 г грибов (шампин
