hf_model/README.md

# Mini GPT1 Clone

This is a decoder-only transformer model (GPT1-style) trained from scratch using PyTorch.

## Model Details

- **Architecture**: Decoder-only Transformer
- **Layers**: 6
- **Embedding Size**: 512
- **Heads**: 8
- **Feedforward Dim**: 2048
- **Sequence Length**: 256
- **Vocab Size**: 35,000

## Tokenizer

Trained using `ByteLevelBPETokenizer` from the `tokenizers` library.

## Inference Example

```python
from transformers import PreTrainedTokenizerFast, AutoModelForCausalLM
import torch

tokenizer = PreTrainedTokenizerFast(tokenizer_file="tokenizer/tokenizer.json")
model = AutoModelForCausalLM.from_pretrained("dilip025/mini-gpt1")

prompt = "Once upon a time,"
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
outputs = model.generate(input_ids, max_length=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
License
MIT