Summarization
Transformers
TensorBoard
Safetensors
t5
text2text-generation
code
flan-t5-small
text-generation-inference
Instructions to use AyeshaFayyaz/t5-small-finetuned-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyeshaFayyaz/t5-small-finetuned-xsum 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="AyeshaFayyaz/t5-small-finetuned-xsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AyeshaFayyaz/t5-small-finetuned-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("AyeshaFayyaz/t5-small-finetuned-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a73d4d077c31287ccdfd2ba58881d6bd3dd14be6cdb1d957e39f8fed4aefa44e
- Size of remote file:
- 242 MB
- SHA256:
- 18bde1e2601627a98f0e8d64353872dca8759dc2fc71394d74cb4891b7275a5a
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