Instructions to use JimmyPin/mt5-finetuned-summarize-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JimmyPin/mt5-finetuned-summarize-small 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-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JimmyPin/mt5-finetuned-summarize-small") model = AutoModelForSeq2SeqLM.from_pretrained("JimmyPin/mt5-finetuned-summarize-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from JimmyPin/mt5-finetuned-summarize-small: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/JimmyPin/mt5-finetuned-summarize-small/resolve/main/training_args.bin
- Command line
-
hf download hf://JimmyPin/mt5-finetuned-summarize-small/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/JimmyPin/mt5-finetuned-summarize-small/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 5ffeb72fb29ed972d60ff649e3995cc7eb07b88cc0014493d7ad2efe3b8424c0
- Size of remote file:
- 5.5 kB
- SHA256:
- 9a54561cbd0d0e777010f2eaf883eea898396204f355539743cc38d040014b5a
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