Instructions to use hf-internal-testing/tiny-random-led with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-led with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-led")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-led") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-led") - Notebooks
- Google Colab
- Kaggle
Please add a proper usage example
#1
by MonsterMMORPG - opened
Add a proper usage with explaining the hyper parameters
I want to summarize 16k tokens into like 800 words
Hi,
This model is only created for test purposes inside the Transformer's library. It has randomly initialized weights.
I suggest to take a look at official LED checkpoints like this one: https://huggingface.co/allenai/led-base-16384.