Summarization
Transformers
PyTorch
Enawené-Nawé
pegasus
text2text-generation
Trained with AutoTrain
Prompt Generation
prompt-generator
text generator
Instructions to use SamAct/PromptGeneration-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamAct/PromptGeneration-base 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="SamAct/PromptGeneration-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SamAct/PromptGeneration-base") model = AutoModelForSeq2SeqLM.from_pretrained("SamAct/PromptGeneration-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add evaluation results on the fabiochiu--medium-articles config and train split of fabiochiu/medium-articles
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\ Your model has been evaluated on the fabiochiu--medium-articles config and train split of the [fabiochiu/medium-articles](https://huggingface.co/datasets/fabiochiu/medium-articles) dataset by @SamAct, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-eval-fabiochiu__medium-articles-fabiochiu__medium-articles-5207ae-64303145522).\ Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=fabiochiu/medium-articles).\ Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=fabiochiu/medium-articles).ad43bee
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Commit From AutoTrain
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initial commit
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