--- language: - en license: apache-2.0 tags: - gpt2 - pytorch - causal-lm - text-generation - alpaca - instruction-following datasets: - tatsu-lab/alpaca base_model: koganrath/LiteGPT-Base --- # LiteGPT-Instruct This is a **124M parameter** Language Model (GPT-2 Small architecture) fine-tuned on the **Alpaca** dataset for instruction following. It is part of the "Small Language Model (SLM)" project, trained from scratch on educational data (FineWeb-Edu) and then fine-tuned on instructions. ## Model Details - **Architecture**: GPT-2 Small (12 layers, 12 heads, 768 embedding dim) - **Parameters**: ~124 Million - **Context Length**: 1024 tokens - **Training**: - **Pre-training**: 10B tokens from [FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) - **Fine-tuning**: [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) dataset (Instruction Tuning) ## Usage This model requires a specific prompt format to function correctly. ### Prompt Template (Alpaca) ```text Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {your_instruction} ### Response: ``` ### Python Example ```python from transformers import GPT2LMHeadModel, GPT2Tokenizer model = GPT2LMHeadModel.from_pretrained("koganrath/LiteGPT-Instruct") tokenizer = GPT2Tokenizer.from_pretrained("gpt2") instruction = "List three primary colors." prompt = f"""Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {instruction} ### Response: """ inputs = tokenizer(prompt, return_tensors="pt") outputs = model.generate(**inputs, max_new_tokens=50) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ``` ## Limitations - **Size**: As a 124M parameter model, its reasoning capabilities are limited compared to larger models (7B+). - **Hallucinations**: It may generate incorrect or nonsensical information. - **Bias**: It inherits biases present in the FineWeb and Alpaca datasets. ## Authors Trained by **koganrath** as part of the LiteGPT Project.