Instructions to use Joemgu/mlong-t5-base-sumstew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joemgu/mlong-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/mlong-t5-base-sumstew")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Joemgu/mlong-t5-base-sumstew") model = AutoModelForSeq2SeqLM.from_pretrained("Joemgu/mlong-t5-base-sumstew") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f3b77dfee20d42dbfb74bb59b4a77bd71ff0573bf0dfd1cd405401d2d1c4eba
- Size of remote file:
- 2.37 GB
- SHA256:
- 485523d0b25487f4a3d1b4546753423187678c8f9d2e0c8e59a5bb81d3922724
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