Instructions to use Hansollll/summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hansollll/summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Hansollll/summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Hansollll/summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Hansollll/summarization: direct link, hf CLI and curl.
- Browser
- Download file 326 Bytes
-
https://huggingface.co/Hansollll/summarization/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Hansollll/summarization/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Hansollll/summarization/resolve/main/tokenizer_config.json
326 Bytes
| { | |
| "model_max_length": 1000000000000000019884624838656, | |
| "name_or_path": "gogamza/kobart-base-v2", | |
| "special_tokens_map_file": "/Users/hansol/.cache/huggingface/hub/models--gogamza--kobart-base-v2/snapshots/f9f2ec35d3c32a1ecc7a3281f9626b7ec1913fed/special_tokens_map.json", | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |