Summarization
Transformers
PyTorch
Safetensors
Japanese
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use p1atdev/t5-base-xlsum-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p1atdev/t5-base-xlsum-ja 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="p1atdev/t5-base-xlsum-ja")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("p1atdev/t5-base-xlsum-ja") model = AutoModelForSeq2SeqLM.from_pretrained("p1atdev/t5-base-xlsum-ja", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from p1atdev/t5-base-xlsum-ja: direct link, hf CLI and curl.
- Browser
- Download file 2.43 MB
-
https://huggingface.co/p1atdev/t5-base-xlsum-ja/resolve/main/tokenizer.json
- Command line
-
hf download hf://p1atdev/t5-base-xlsum-ja/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/p1atdev/t5-base-xlsum-ja/resolve/main/tokenizer.json
2.43 MB
File too large to display, you can check the raw version instead.