Summarization
Transformers
PyTorch
JAX
Core ML
English
t5
text2text-generation
wikihow
t5-small
lm-head
seq2seq
pipeline:summarization
text-generation-inference
Instructions to use osanseviero/t5-finetuned-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osanseviero/t5-finetuned-test 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="osanseviero/t5-finetuned-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("osanseviero/t5-finetuned-test") model = AutoModelForSeq2SeqLM.from_pretrained("osanseviero/t5-finetuned-test") - Notebooks
- Google Colab
- Kaggle
- Size of remote file:
- 242 MB
- SHA256:
- 839172ec1b0268b1036d1c5c9806338bc67e3a6b67238a66f15c25fa151edd9f
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