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") - Notebooks
- Google Colab
- Kaggle
Add special_tokens_map.json from allenai/led-base-16384
Browse files- special_tokens_map.json +1 -0
special_tokens_map.json
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{"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}}
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