Instructions to use tranv/mt5-base-finetuned-sumeczech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tranv/mt5-base-finetuned-sumeczech 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="tranv/mt5-base-finetuned-sumeczech")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tranv/mt5-base-finetuned-sumeczech") model = AutoModelForSeq2SeqLM.from_pretrained("tranv/mt5-base-finetuned-sumeczech") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cffc80d5bd85992fa0969699c02f9dcc73fa22271ca647017eec1056e4ff291e
- Size of remote file:
- 4.73 kB
- SHA256:
- 830970a3f4ec87b864cbb87332830f1b0a927675c3763bb5023fff251e778c1a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.