Summarization
Transformers
Safetensors
English
bart
text2text-generation
news
abstractive-summarization
Instructions to use aniket23/news_scraper_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aniket23/news_scraper_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="aniket23/news_scraper_model", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("aniket23/news_scraper_model") model = AutoModelForSeq2SeqLM.from_pretrained("aniket23/news_scraper_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 458e4194571a98fb7e4b5d354a3d7059eb524d3358c2d142f29a878d6fcdf66b
- Size of remote file:
- 6.03 kB
- SHA256:
- 1d563e57a967ef0860fa8b947a457c336c6b54a8514b3955dbd695d2497cf27b
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