Instructions to use QQhahaha/Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QQhahaha/Summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("QQhahaha/Summarization") model = AutoModelForSeq2SeqLM.from_pretrained("QQhahaha/Summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from QQhahaha/Summarization: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/QQhahaha/Summarization/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://QQhahaha/Summarization@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/QQhahaha/Summarization/resolve/refs%2Fpr%2F1/tokenizer.json
16.3 MB
- Xet hash:
- 5684f412d913e005c160e4ad89148e537e0c4a100b9f1efa1b66dcdbb7e01479
- Size of remote file:
- 16.3 MB
- SHA256:
- 962ff7570fd5e96d6af4a09008a269437c7933289162dca163a4dd92e2c4502a
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