Welcome to the GPT3 repository! This project is an attempt to recreate the architecture and approach from the original OpenAI GPT-3 paper. The repository includes scripts for training, fine-tuning, and inference of a GPT-3-like model using PyTorch and the Hugging Face Transformers library.
Here are located weights of dev checkpoints of my models. You can always download a folder, paste it's path inside inference.py and chat with them.
1from transformers import AutoTokenizer, AutoModelForCausalLM
2model = AutoModelForCausalLM.from_pretrained('k050506koch/GPT3-dev-125m-0104', trust_remote_code=True)
3tokenizer = AutoTokenizer.from_pretrained('k050506koch/GPT3-dev-125m-1202')
4tokenizer.pad_token_id = tokenizer.eos_token_id
5print("\n", tokenizer.decode(model.generate(tokenizer.encode("He is a doctor. His main goal is", return_tensors='pt'),
6 max_length=128, temperature=0.7, top_p=0.9, repetition_penalty=1.2, no_repeat_ngram_size=3,
7 num_return_sequences=1, do_sample=True)[0], skip_special_tokens=True))
Please note that the model is not trained for continious chat and not tested for it so it's possible but unlikely that it will keep the topic and act coherently between messages.
Contributions are welcome! I'm just a student who is interested in AI so my code may be incorrect or have logical issues. Please open an issue or submit a pull request for any improvements or bug fixes, I will be happy.
This project is licensed under the MIT License. See the LICENSE file for details. Everyone can use and modify this code at their discretion.