Instructions to use Joemgu/long-t5-base-sumstew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joemgu/long-t5-base-sumstew 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="Joemgu/long-t5-base-sumstew")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Joemgu/long-t5-base-sumstew") model = AutoModelForSeq2SeqLM.from_pretrained("Joemgu/long-t5-base-sumstew") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the samsum config and test split of samsum
#3
by autoevaluator HF Staff - opened
Beep boop, I am a bot from Hugging Face's automatic model evaluator π!
Your model has been evaluated on the samsum config and test split of the samsum dataset by @baohuynhbk14 , using the predictions stored here.
Accept this pull request to see the results displayed on the Hub leaderboard.
Evaluate your model on more datasets here.
Joemgu changed pull request status to merged