Summarization
Transformers
PyTorch
Enawené-Nawé
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use aszfcxcgszdx/summarizer_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aszfcxcgszdx/summarizer_v3 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="aszfcxcgszdx/summarizer_v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("aszfcxcgszdx/summarizer_v3") model = AutoModelForSeq2SeqLM.from_pretrained("aszfcxcgszdx/summarizer_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10f0344ffecc5a3dd0650d2d3473a25f87b00b77123aca4a1811641ec0a2549a
- Size of remote file:
- 3.13 GB
- SHA256:
- c773fb3f0667d5c546902b2a26184851ecc274358119dee5b38e94c71d857479
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