3 март 2024 г
(Този текст е автоматично генериран от модела от английската версия на блога. [*])
В INSAIT сме развълнувани да пуснем BgGPT-7B-Instruct-v0.2, модела, който стои зад приложението за чат BgGPT: https://chat.bggpt.ai. Този модел, част от серията BgGPT, е подобрена версия на тази, която пуснахме преди няколко седмици. BGGPT-7B-Instruct-v0.2 все още е 7B модел, което го прави много бърз за генериране на текст и може да работи на повечето съвременни персонални компютри. Освен това идва с лиценз Apache 2.0, който е свободен и подходящ за търговски цели. Моделът се основава на Mistral-7B, но беше обучен върху значителни количества данни и комбиниран с други нововъведения (които ще бъдат публикувани в изследователски конференции), може да надмине много по-големи модели на задачи на български език. Обучението на BGGPT-7B-Instruct-v0.2 се финансира изцяло от частни средства и дарения. Моля, вижте блога ни за BGGPT-7B-Instruct-v0.1, който пуснахме по-рано.
През последните 2 седмици BGGPT-7B-Instruct-v0.1 вече е приет от различни компании, които са коментирали, че с малко часове работа и ниски разходи за изчислителни ресурси за фина настройка, той може да достигне производителността на GPT-4 на конкретна задача на български език.
Както при много други езикови модели, ние оценяваме на набор от стандартни превeдени на български тестове, както и английски тестове:
Тези тестове тестват логическото разсъждение, математическите умения, знанията, разбирането на езика и други умения на модела.
Следните графики показват представянето на BgGPT-7B-Instruct-v0.2. Той надминава моделите със същия размер на българските бенчмаркове, включително подобрява предишната версия на BgGPT-7B (BGGPT-7B-Instruct-v0.1). Той също така надмина по-големия Mixtral-8x7B-Instruct-v0.1 на българските бенчмаркове. Той запази своите английски умения и в някои отношения е сравним или по-добър от моделите на Gemma-7B на Google, Mistral-7B, Llama-7B и др.
Въпреки че моделът е доста конкурентен на безплатните отворени модели и особено като се има предвид неговият размер, той все още не е на нивото на комерсиалните платени предложения. Въпреки това, дори на сегашното си ниво, той може да бъде полезен за много приложения.
[*] Преводът е извършен в 2 стъпки. Първо попитахме: “Преведи на български език следния текст:” и поставяме английската версия на текста без заглавието. След това в същия чат попитахме “Направи го да звучи по-точно”.
March 3, 2024
At INSAIT we are delighted to release BgGPT-7B-Instruct-v0.2, the model used behind the BgGPT chat app: https://chat.bggpt.ai. This model, part of the BgGPT series of models, is an improved version of the one we released a couple of weeks ago. BGGPT-7B-Instruct-v0.2 is still a 7B model, which is very fast for text generation and can run on most recent personal computers. It also comes with a permissive and commercial-friendly Apache 2.0 licence. The model is based on Mistral-7B, but was trained on significant amounts of data, and combined with other advances (to be published in research conferences), can outperform much larger models on Bulgarian tasks. The training costs of BGGPT-7B-Instruct-v0.2 come entirely from private funds and donations. Please see the blog post for BGGPT-7B-Instruct-v0.1 we released earlier.
In only 2 weeks, BGGPT-7B-Instruct-v0.1 has already been adopted by various companies who remarked that with only few hours of work and low computation and financial resources for fine-tuning, it can reach the performance of GPT-4 on a particular task in Bulgarian.
As with many other language models, we evaluate on a set of standard benchmarks translated to Bulgarian as well as on English benchmarks:
These benchmarks test the logical reasoning, math, knowledge, language understanding and other skills of the model.
The following graphs show the performance of BgGPT-7B-Instruct-v0.2. It outperforms same-sized models on Bulgarian benchmarks, including improving upon the previous version of BgGPT-7B (BGGPT-7B-Instruct-v0.1). It also outperformed the much larger Mixtral-8x7B-Instruct-v0.1 on Bulgarian benchmarks. It also did not lose English skills and on some is comparable or better than the models of Google’s Gemma-7B, Mistral-7B, Llama-7B and others.
Note that while the model is quite competitive to free open-source models, and especially for its size, it is still not on the level of paid commercial offerings. Yet, even at the current level, it can be useful for many applications.
February 18, 2024
At INSAIT we are thrilled to launch BgGPT-7B-Instruct-v0.1, the first free and open Bulgarian Large Language Model in the BgGPT series (more models coming soon). BgGPT-7B-Instruct-v0.1 is now available for download at HuggingFace with the permissive and commercial-friendly Apache 2.0 licence. The model, which builds on Mistral-7B, already outperforms similarly sized models such as LLaMA2-7b and Mistral-7B on all Bulgarian language tasks. On many of these tasks, It also outperforms much larger models such as Mixtral-8x7B-Instruct-v0.1 (about 6.5 times larger), which has been shown to have similar capabilities as GPT-3.5.
To systematically evaluate the Bulgarian performance of LLMs, including our model and any existing or future models, we translated a set of benchmarks to Bulgarian, including:
These benchmarks (except the last one which already exists) were built via both machine translation as well as our amazing team of translators. For evaluation, we forked a version of the EuletherAI's evaluation harness. All benchmark data is made publicly available in our HF repository to help others evaluate their own models.
Note on evaluation: great care should be taken to not contaminate training or fine-tuning datasets by including the above benchmarks (generally known as overfitting, but a threat recently explored in detail here [9]), which can lead to misreported results.
The following graphs show the performance of BgGPT-7B-Instruct-v0.1. It clearly outperforms same-sized models on Bulgarian benchmarks as well as on most other benchmarks. It also outperformed the much larger Mixtral-8x7B-Instruct-v0.1 on Bulgarian benchmarks. That said, the model does not excel at deep reasoning and knowledge skills, though this is somewhat expected as smaller models can learn less which is reflected in the knowledge-testing benchmarks. We expect this to improve in the BgGPT that will follow. Interestingly, even though the model is biased to Bulgarian, it does retain some English skills, making it a versatile tool for cross-lingual tasks including translation from English to Bulgarian. Here we include a gist of the benchmark results.
While larger models will in general offer superior performance, we see that specialised, smaller 7B models can actually produce similar results to non-specialized much larger models, while enjoying much cheaper inference costs. Further, for many business applications, smaller models may suffice. Over the next weeks, we will release improved models, so stay tuned!
If you are an institution or a business organisation interested in using BgGPT internally and have questions on how to do so, please contact us at: bggpt@insait.ai