Instructions to use yohannesahunm/amharic_text_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yohannesahunm/amharic_text_summarization 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="yohannesahunm/amharic_text_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yohannesahunm/amharic_text_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("yohannesahunm/amharic_text_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from yohannesahunm/amharic_text_summarization: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/yohannesahunm/amharic_text_summarization/resolve/main/tokenizer.json
- Command line
-
hf download hf://yohannesahunm/amharic_text_summarization/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/yohannesahunm/amharic_text_summarization/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 75581306d37e78cec3d0db3382e555b023bb8e7394b63598769b2dc2e66d6818
- Size of remote file:
- 16.3 MB
- SHA256:
- 98e28d7e54a4b3bb33f8a6fb43290605605c89d13c8df5fe9fde9bc9e01e09b2
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