Summarization
Transformers
PyTorch
English
led
text2text-generation
text-generation
encoder-decoder
longformer
bart
abstractive-summarization
news-summarization
research-summarization
document-summarization
english
NLP
Instructions to use assemsabry/Research-News-AI-Summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use assemsabry/Research-News-AI-Summarizer 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="assemsabry/Research-News-AI-Summarizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("assemsabry/Research-News-AI-Summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("assemsabry/Research-News-AI-Summarizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27208f578e8e3d9edb8f4cf6abbca6dedf4842f9bfe8809a6f108fe43b90145b
- Size of remote file:
- 257 MB
- SHA256:
- a56093836f6283ceac48128515f6c87ade70abb11aec31d23a176c4d90ae1736
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