| Model trained on the TinyStories Dataset, see https://arxiv.org/abs/2305.07759 | |
| ------ EXAMPLE USAGE --- | |
| from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig | |
| model = AutoModelForCausalLM.from_pretrained('roneneldan/TinyStories-1M') | |
| tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M") | |
| prompt = "Once upon a time there was" | |
| input_ids = tokenizer.encode(prompt, return_tensors="pt") | |
| # Generate completion | |
| output = model.generate(input_ids, max_length = 1000, num_beams=1) | |
| # Decode the completion | |
| output_text = tokenizer.decode(output[0], skip_special_tokens=True) | |
| # Print the generated text | |
| print(output_text) | |
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | |
| Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_roneneldan__TinyStories-1M) | |
| | Metric | Value | | |
| |-----------------------|---------------------------| | |
| | Avg. | 25.02 | | |
| | ARC (25-shot) | 23.46 | | |
| | HellaSwag (10-shot) | 25.23 | | |
| | MMLU (5-shot) | 24.57 | | |
| | TruthfulQA (0-shot) | 49.4 | | |
| | Winogrande (5-shot) | 52.17 | | |
| | GSM8K (5-shot) | 0.0 | | |
| | DROP (3-shot) | 0.32 | | |