Summarization
Transformers
PyTorch
Enawené-Nawé
longt5
text2text-generation
Trained with AutoTrain
Eval Results (legacy)
Instructions to use Jacobsith/autotrain-Hello_there-1209845735 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jacobsith/autotrain-Hello_there-1209845735 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="Jacobsith/autotrain-Hello_there-1209845735")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jacobsith/autotrain-Hello_there-1209845735") model = AutoModelForSeq2SeqLM.from_pretrained("Jacobsith/autotrain-Hello_there-1209845735") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d8a7588aac5eb96e9eaf5ba4842ceec4ac191e2a7890ce8a44be6dc00e6ec1a
- Size of remote file:
- 3.13 GB
- SHA256:
- dd3eedb16c351c8ca1b883ea5faf7e6fb74f633f205cf588afa531bec6b9bf59
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