Summarization
Transformers
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text2text-generation
natural-language-processing
text-summarization
machine-learning
deep-learning
transformer
artificial-intelligence
text-analysis
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tensorflow
text-generation-inference
Instructions to use 2KKLabs/Lacia_sum_small_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 2KKLabs/Lacia_sum_small_v1 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="2KKLabs/Lacia_sum_small_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("2KKLabs/Lacia_sum_small_v1") model = AutoModelForSeq2SeqLM.from_pretrained("2KKLabs/Lacia_sum_small_v1") - Notebooks
- Google Colab
- Kaggle
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