metadata
base_model: HuggingFaceTB/SmolLM2-360M
library_name: transformers
model_name: SmolLM2-360M-tldr-sft-2025-02-12_15-13
tags:
- generated_from_trainer
- trl
- sft
license: mit
Smol-Hub-tldr
This model is a fine-tuned version of HuggingFaceTB/SmolLM2-360M. The model is focused on generating concise, one-sentence summaries of model and dataset cards from the Hugging Face Hub. These summaries are intended to be used for:
- creating useful tl;dr descriptions that can give you a quick sense of what a dataset or model is for
- as input text for creating embeddings for semantic search. You can see a demo of this in librarian-bots/huggingface-datasets-semantic-search.
The model was trained using supervised fine-tuning (SFT) with TRL.
Intended Use
The model is designed to generate brief, informative summaries of:
- Model cards: Focusing on key capabilities and characteristics
- Dataset cards: Capturing essential dataset characteristics and purposes
Training Data
The model was trained on:
- Model card summaries generated by Llama 3.3 70B
- Dataset card summaries generated by Llama 3.3 70B
Usage
from transformers import pipeline
generator = pipeline("text-generation", model="davanstrien/SmolLM2-360M-tldr-sft-2025-02-12_15-13", device="cuda")
output = generator(input_text, max_new_tokens=128, return_full_text=False)[0]
Framework Versions
- TRL 0.14.0
- Transformers 4.48.3
- PyTorch 2.6.0
- Datasets 3.2.0
- Tokenizers 0.21.0