Instructions to use GregSamek/TinyNews-11M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GregSamek/TinyNews-11M with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GregSamek/TinyNews-11M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from GregSamek/TinyNews-11M: direct link, hf CLI and curl.
- Browser
- Download file 908 Bytes
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https://huggingface.co/GregSamek/TinyNews-11M/resolve/main/README.md
- Command line
-
hf download hf://GregSamek/TinyNews-11M/README.md
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curl -L -o README.md https://huggingface.co/GregSamek/TinyNews-11M/resolve/main/README.md
908 Bytes
metadata
datasets:
- GregSamek/TinyNews
language:
- en
Tiny News
For a detailed overview of this project from start to finish, check out GregSamek.github.io/TinyNews
TinyNews is a collection of one million synthetically generated news bulletins and several language models scratch-trained on this data. Evaluations suggests that TinyNews retains ~80% of the quality of the training data while using ~1/1000th the number of parameters as the models used to generate it.
To run these models, git clone the repository
Trained models and training data are available in this 🤗 Hugging Face Collection
This project is essentially a modified reimplementation of the Microsoft Research TinyStories project.