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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8e243bcb30470a72c5917b93260387799b9221c3575221c8ea269eb760fa7fc
- Size of remote file:
- 16.8 MB
- SHA256:
- 750ffbacc45c2f284f16da1d281fedfe2ed16f956306c0999ccaeb7b08554793
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