---
license: mit
base_model: openai-community/gpt2
datasets:
- OpenAssistant/oasst1
language:
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- gpt2
- gpt-2
- chatbot
- text-generation-inference
---

# GPT-2 SFT on OASST1

This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the [OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1) dataset.

## Training Procedure

- **Base Model:** GPT-2 Small (124M parameters)
- **Dataset:** OpenAssistant OASST1 (English only)
- **Format:** `user: ... assistant: <s> ... </s>`
- **Epochs:** 15
- **Learning Rate:** 5e-5
- **Batch Size:** 4 (effective 16 with gradient accumulation)

## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "gitcoreai/gpt-2-small-sft"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "user: hello, how are you?\nassistant: <s>"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=60)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))