Instructions to use BardakAI/BARDAKAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use BardakAI/BARDAKAI with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r BardakAI/BARDAKAI -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
|
Download README.md from BardakAI/BARDAKAI: direct link, hf CLI and curl.
- Browser
- Download file 7.89 kB
-
https://huggingface.co/BardakAI/BARDAKAI/resolve/main/README.md
- Command line
-
hf download hf://BardakAI/BARDAKAI/README.md
-
curl -L -o README.md https://huggingface.co/BardakAI/BARDAKAI/resolve/main/README.md
7.89 kB
| license: mit | |
| language: | |
| - tr | |
| base_model: | |
| - BardakAI/BARDAKAI | |
| new_version: BardakAI/BARDAKAI | |
| pipeline_tag: question-answering | |
| library_name: sample-factory | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). | |
| ## Model Details | |
| ### Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** [kozasoft-dağlar ali koç]] | |
| - **Funded by [optional]:** [Dağlar Ali K.] | |
| - **Shared by [optional]:** [Kozasoft] | |
| - **Model type:** [Dil modeli (LLM)transformer tabanlı] | |
| - **Language(s) (NLP):** [TÜRKÇE (TR)] | |
| - **License:** [MİT VEYA APACHE 2.0] | |
| - **Finetuned from model [optional]:** [HAYIR SIFIRDAN EĞİTİLDİ] | |
| ### Model Sources [optional] | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** [] | |
| - **Paper [optional]:** [More Information Needed] | |
| - **Demo [optional]:** [https://sites.google.com/view/bardak-gpt/home] | |
| ## Uses | |
| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> | |
| ### Direct Use | |
| <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> | |
| [BARDAKAI, Türkçe doğal dil işleme görevleri için tasarlanmıştıt .Soru-cevap ,metin üretimi,sohbet ve temel dil görevlerinde kullanlıbalilir .günlük sohbet asistanı gbii alanlarda etkilidir.## Downstream Use [optional] | |
| <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> | |
| [More Information Needed] | |
| ### Out-of-Scope Use | |
| <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> | |
| [Yüksek doğruluk gerektiren krtitik kararlar, | |
| yasadışı ve zararlı ,nefret söylemi içeren icerik üretimi ,hukiki danışmanlık] | |
| ## Bias, Risks, and Limitations | |
| <!-- This section is meant to convey both technical and sociotechnical limitations. --> | |
| [BardakAI 25 milyon parametreli küçük bir modeldir. Bu nedenle: | |
| · Bilgi sınırı: Sadece eğitildiği verilerle sınırlıdır, güncel bilgilere erişimi yoktur. | |
| · Halüsinasyon: Yanlış veya uydurma bilgi üretebilir. | |
| · Önyargı: Eğitim verisindeki önyargıları yansıtabilir. | |
| · Bağlam sınırı: Uzun konuşmalarda bağlamı kaybedebilir. | |
| · Dil sınırı: Ağırlıklı olarak Türkçe odaklıdır, diğer dillerde zayıftır. | |
| · Karmaşık görevler: Matematik, kod yazma gibi alanlarda sınırlıdır.] | |
| ### Recommendations | |
| <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> | |
| Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. | |
| ## How to Get Started with the Model | |
| Use the code below to get started with the model. | |
| [ Modele Nasıl Başlanır? | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| tokenizer = AutoTokenizer.from_pretrained("kozasoft/bardakai") | |
| model = AutoModelForCausalLM.from_pretrained("kozasoft/bardakai") | |
| input_text = "Merhaba, nasılsın?" | |
| inputs = tokenizer(input_text, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_length=100) | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True))] | |
| ## Training Details | |
| ### Training Data | |
| <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> | |
| [Eğitim Verileri: | |
| Türkçe metin korpusu, açık kaynak veri setleri ve özenle seçilmiş örnek cümleler. | |
| Eğitim Prosedürü: | |
| · Ön işleme: Metin temizleme, tokenizasyon, normalizasyon | |
| · Eğitim Platformu: Google Colab | |
| · Eğitim Süresi: ~2.5 milyar token | |
| Eğitim Hiperparametreleri: | |
| · Learning rate: 3e-4 | |
| · Batch size: 8 | |
| · Epoch: 3 | |
| · Optimizer: AdamW | |
| · Mimari: Transformer (hafif yapı) | |
| ] | |
| ### Training Procedure | |
| <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> | |
| #### Preprocessing [optional] | |
| [More Information Needed] | |
| #### Training Hyperparameters | |
| - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> | |
| #### Speeds, Sizes, Times [optional] | |
| <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> | |
| [More Information Needed] | |
| ## Evaluation | |
| <!-- This section describes the evaluation protocols and provides the results. --> | |
| ### Testing Data, Factors & Metrics | |
| #### Testing Data | |
| <!-- This should link to a Dataset Card if possible. --> | |
| [More Information Needed] | |
| #### Factors | |
| <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> | |
| [More Information Needed] | |
| #### Metrics | |
| <!-- These are the evaluation metrics being used, ideally with a description of why. --> | |
| [More Information Needed] | |
| ### Results | |
| [BardakAI, KOZASOFT Ekibi tarafından geliştirilen 25 milyon parametreli, hafif ve optimize edilmiş bir Türkçe dil modelidir. Google Colab üzerinde eğitilmiştir. Anonim kullanım, gizlilik odaklı tasarım ve hızlı yanıt üretimi öncelikli hedefleridir.] | |
| #### Summary | |
| ## Model Examination [optional] | |
| <!-- Relevant interpretability work for the model goes here --> | |
| [More Information Needed] | |
| ## Environmental Impact | |
| <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> | |
| Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). | |
| - **Hardware Type:** [GOOGLE COLAB T4 GPU] | |
| - **Hours used:** [a few hours] | |
| - **Cloud Provider:** [GOOGLE COLAB] | |
| - **Compute Region:** [GLOBAL] | |
| - **Carbon Emitted:** [DÜŞÜK VEYA HİÇE YAKIN] | |
| ## Technical Specifications [optional] | |
| ### Model Architecture and Objective | |
| [More Information Needed] | |
| ### Compute Infrastructure | |
| [More Information Needed] | |
| #### Hardware | |
| [More Information Needed] | |
| #### Software | |
| [More Information Needed] | |
| ## Citation [optional] | |
| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> | |
| **BibTeX:** | |
| [More Information Needed] | |
| **APA:** | |
| [More Information Needed] | |
| ## Glossary [optional] | |
| <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> | |
| [More Information Needed] | |
| ## More Information [optional] | |
| [BardakAI 25 milyon parametreli küçük bir modeldir. Bu nedenle: | |
| · Bilgi sınırı: Sadece eğitildiği verilerle sınırlıdır, güncel bilgilere erişimi yoktur. | |
| · Halüsinasyon: Yanlış veya uydurma bilgi üretebilir. | |
| · Önyargı: Eğitim verisindeki önyargıları yansıtabilir. | |
| · Bağlam sınırı: Uzun konuşmalarda bağlamı kaybedebilir. | |
| · Dil sınırı: Ağırlıklı olarak Türkçe odaklıdır, diğer dillerde zayıftır. | |
| · Karmaşık görevler: Matematik, kod yazma gibi alanlarda sınırlıdır.]] | |
| ## Model Card Authors [optional] | |
| [İletişim: bardakgpt@gmail.com | |
| Kurumsal: info.kozasoft@gmail.com | |
| Demo: https://bardakai.tiiny.site | |
| websitesi:https://sites.google.com/view/bardak-gpt/home] | |
| ## Model Card Contact | |
| [KOZASOFT Ekibi – BardakAI Geliştirme Ekibi | |
| 📧 Model Kart İletişim Bilgileri | |
| E-posta: bardakgpt@gmail.com | |
| Kurumsal: info.kozasoft@gmail.com | |
| ] |