Instructions to use YasirAbdali/bart-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YasirAbdali/bart-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("YasirAbdali/bart-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("YasirAbdali/bart-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from YasirAbdali/bart-summarization: direct link, hf CLI and curl.
- Browser
- Download file 262 Bytes
-
https://huggingface.co/YasirAbdali/bart-summarization/resolve/main/generation_config.json
- Command line
-
hf download hf://YasirAbdali/bart-summarization/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/YasirAbdali/bart-summarization/resolve/main/generation_config.json
262 Bytes
| { | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 2, | |
| "early_stopping": true, | |
| "eos_token_id": 2, | |
| "forced_bos_token_id": 0, | |
| "forced_eos_token_id": 2, | |
| "no_repeat_ngram_size": 3, | |
| "num_beams": 4, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.42.3" | |
| } | |