Instructions to use JimmyPin/mt5-finetuned-summarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JimmyPin/mt5-finetuned-summarize 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="JimmyPin/mt5-finetuned-summarize")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JimmyPin/mt5-finetuned-summarize") model = AutoModelForSeq2SeqLM.from_pretrained("JimmyPin/mt5-finetuned-summarize", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from JimmyPin/mt5-finetuned-summarize: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/JimmyPin/mt5-finetuned-summarize/resolve/main/training_args.bin
- Command line
-
hf download hf://JimmyPin/mt5-finetuned-summarize/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/JimmyPin/mt5-finetuned-summarize/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 53c06ee57a32dc9ae0ee7c3a5a0c01e5796a66ef0ef2e77162803016e5349971
- Size of remote file:
- 5.5 kB
- SHA256:
- 6df5e09ecb48d5ff8206ced1581b9f333e927e0dfce535c14d32c5997b4e230f
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