Instructions to use praf-choub/bart-CaPE-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use praf-choub/bart-CaPE-cnn 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="praf-choub/bart-CaPE-cnn")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("praf-choub/bart-CaPE-cnn") model = AutoModelForSeq2SeqLM.from_pretrained("praf-choub/bart-CaPE-cnn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from praf-choub/bart-CaPE-cnn: direct link, hf CLI and curl.
- Browser
- Download file 239 Bytes
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https://huggingface.co/praf-choub/bart-CaPE-cnn/resolve/main/special_tokens_map.json
- Command line
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hf download hf://praf-choub/bart-CaPE-cnn/special_tokens_map.json
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curl -L -o special_tokens_map.json https://huggingface.co/praf-choub/bart-CaPE-cnn/resolve/main/special_tokens_map.json
239 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}} |