Summarization
Transformers
Safetensors
English
t5
text2text-generation
summer
huggingface
text-generation-inference
Instructions to use Lazabriellholland/summer-summary-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lazabriellholland/summer-summary-model 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="Lazabriellholland/summer-summary-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Lazabriellholland/summer-summary-model") model = AutoModelForSeq2SeqLM.from_pretrained("Lazabriellholland/summer-summary-model") - Notebooks
- Google Colab
- Kaggle
βοΈ Summer Summary Model
A fine-tuned version of t5-small trained on scene summaries from the first 5 episodes of The Summer I Turned Pretty. This model turns scene descriptions or dialogue into short, clear summaries.
π‘ How to Use
Try it live on the Hugging Face π€ model page (scroll down to the input box below), or use the code:
from transformers import pipeline
summarizer = pipeline("summarization", model="Lazabriellholland/summer-summary-model")
text = "Belly and Conrad talk on the beach about last summer."
summary = summarizer(text)[0]['summary_text']
print(summary)
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