Instructions to use mogesa/amharic_summarization_mt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mogesa/amharic_summarization_mt5 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="mogesa/amharic_summarization_mt5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mogesa/amharic_summarization_mt5") model = AutoModelForSeq2SeqLM.from_pretrained("mogesa/amharic_summarization_mt5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97720acfff94f43834b1df850842f8e87f7d57c1d891afaaa04788477194d302
- Size of remote file:
- 1.2 GB
- SHA256:
- d2ba09b9e35f0d69f792eefa7adcfa8bd02ad87d0d5dc3ac4610d1f35fe56a96
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