--- license: cc-by-nc-4.0 pipeline_tag: text-generation library_name: transformers tags: - chat - text-generation-inference new_version: Bertug1911/BrtGPT-124m-FineTuned --- # BrtGPT-124M-Base ***NOTE: MODEL TRAINED ON 5M TOKENS AGAIN IN 14 JUNE 2025, IF YOU DOWNLOADED WEIGHTS BEFORE; REINSTALL!*** * This model trained on 5M (About 5.000.000) Tokens, With "English" Sentences. * Model ***IS NOT*** for QA (UNLIKE ChatGPT or LLama), this model is only ***Pre-Trained*** on ***Large Corpus***, so this is a ***Base Model*** ## Model Details ### Model Description CHECK THE COMMUNITY FOR VERY IMPORTANT UPDATES! - **Developed by:** Bertug Gunel (Bertuğ Günel) - **Funded by [optional]:** Nobody - **Shared by [optional]:** Nobody - **Model type:** Decoder-Only Transformer - **Language(s) (NLP):** English - **License:** CC-BY-NC-4.0 - **Finetuned from model [optional]:** Not Fine-Tuned ### Model Sources [optional] - **Repository:** Cooming Soon! - **Paper [optional]:** ***"Attention All You Need"***, ***1706.03762*** - **Demo [optional]:** Model is already a demo model. ## Uses This codes, loads the model (BrtGPT-124M-Base), you can use it! ``` from transformers import AutoTokenizer, AutoModelForCausalLM import torch # Load Model and Tokenizer model_name = "Bertug1911/BrtGPT-124m-Base" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained(model_name) # Input prompt = "Math is so important because" # Tokenize it inputs = tokenizer(prompt, return_tensors="pt") # Generate with model output = model.generate( **inputs, max_new_tokens=50, temperature=0.01, top_k=1, do_sample=True ) # Decode output generated_text = tokenizer.decode(output[0], skip_special_tokens=False) generated_text = generated_text.replace(" ", "") generated_text = generated_text.replace("Ġ", " ") print(generated_text) ``` API USE: ``` from gradio_client import Client client = Client("Bertug1911/BrtGPT-Web-UI") result = client.predict( prompt="Hello!!", temperature=0.5, top_k=10, max_new_tokens=15, api_name="/generate_text" ) print(result) ``` USAGE EXAMPLES: | **Input** | **Max New Tokens** | **Temperature** | **Output** | | :------------: | :------------: | :------------: | :------------: | | "Today" | 50 | 0.1 | "Today, a complex and multifaceted system, is often viewed as a myriad of the intricacies of the human mind and the intricacies of the human condition. It is believed to be a powerful" | | "To stop world hunger, we should" | 50 | 0.1 | "To stop world hunger, we should be able to find a more stable and healthy relationship with the body. By doing so, we can make a mealtime and easier to start and maintain a healthy and balance." | | "Math is so important because" | 50 | 0.1 | "MMath is so important because it's essential to carefully consider and address any potential health concerns that may arise from the condition, as it can lead to a range of health issues. By including the bleeding and potentially causing sympt..." | | "To be rich, you should," | 50 | 0.4 | "To be rich you should be on the same time, it's essential to consider the various factors that contribute to your unique needs. For instance, it's crucial to consider that you should be taking a black room,..." | ### Direct Use Perhaps the worst part of open source models is that using them is very laborious and requires a lot of processing power, but our model solves both problems: you can use and download them for ***FREE*** and ***VERY EASILY*** from the link below! Web (Gradio, Spaces) UI is done! To use it ***FREELY*** and ***EASILY*** Hugging Face Spaces ***LINK: "https://huggingface.co/spaces/Bertug1911/BrtGPT-Web-UI"*** ***NEW***; Web page is now available: "https://brtgpt-chat.netlify.app/" if first site is down, use: "https://sites.google.com/view/brtgpt-offical/" ### Out-of-Scope Use Model only generates (completes) "English" sentences with "English" tokens. (And contains some Japanese/Chinese tokens.) ***Don't try*** with another Languages! ## Bias, Risks, and Limitations Model can generates: "Political" contents, USE YOUR OWN RISK ### Recommendations No big risks or biases! You can use it freely (But only ***"Non-commerical"***) ## How to Get Started with the Model You can use model for generating English texts. Model is ***FREE*** to use. ## Training Details ### Training Data ***NOTE: MODEL TRAINED ON 5M TOKENS AGAIN IN 13 JUNE 2025, IF YOU DOWNLOADED WEIGHTS BEFORE; REINSTALL!*** Model trained on: Train.csv (5M tokens, 15000+ lines) | **Data Type** | **Training Type** | **Tokens (Total)** | **Status** | | :------------: | :------------: | :------------: | :------------: | | Raw (sentences) | Pre Training | About 5M (5000K) | ***FINISHED*** | | Raw (sentences) | Fine-Tuning (For upgrade model performance on tests and usage!) | About 0.1M (100K) | ***FINISHED ON 17 JUNE***| | Instruction (Coming soon!) | Instruction Tuning (IFT) | Cooming soon! | SOON! (Probably; in July (5-15)) | FINE-TUNING DETAILS: ***You can acces fine-tuned model with this link: "https://huggingface.co/Bertug1911/BrtGPT-124m-FineTuned" NOTE: Fine-tuned model has "model.safetensors", this file contains weights (Fine-tuned from this model.)*** ### Training Procedure Model Trained on: B200 GPU (Nvidia) for 21,5 Minutes. #### Training Hyperparameters - **Training regime:** Training precision is: FP16, Sparsity: ***OFF*** ## Evaluation NO EVALUATION (Cooming soon!) ## Environmental Impact 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:** GPU - **Hours used:** 0.35 (21,5 Mins) - **Cloud Provider:** "Runpod" (https://www.runpod.io/) - **Compute Region:** EU - **Carbon Emitted:** 0.138 KG (138 Gram(s)) "This is equivalent to an average light bulb burning for 2.6 hours." ## Model Card Authors [optional] * Bertug Gunel * Turkey/Eskisehir ## Model Card Contact bertugscpmail@gmail.com