Instructions to use johngiorgi/led-base-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use johngiorgi/led-base-16384 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="johngiorgi/led-base-16384")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("johngiorgi/led-base-16384") model = AutoModelForSeq2SeqLM.from_pretrained("johngiorgi/led-base-16384") - Notebooks
- Google Colab
- Kaggle
Model Card
This model is identical to allenai/led-base-16384, except the generation_config.json has been updated from:
{
"_from_model_config": true,
"bos_token_id": 0,
"decoder_start_token_id": 2,
"eos_token_id": 2,
"pad_token_id": 1
}
to
{
"bos_token_id": 0,
"decoder_start_token_id": 2,
"eos_token_id": 2,
"pad_token_id": 1,
"early_stopping": true,
"length_penalty": 2.0,
"max_length": 512,
"min_length": 100,
"no_repeat_ngram_size": 3,
"num_beams": 4
}
which we found to be much more stable when fine-tuning the model for summarization tasks.
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