Instructions to use transformer3/check-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transformer3/check-model 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="transformer3/check-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("transformer3/check-model") model = AutoModelForSeq2SeqLM.from_pretrained("transformer3/check-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed152fa4019e99bc02c1d63c509456787bd552703008bb5c16b3a3c56381fb30
- Size of remote file:
- 1.63 GB
- SHA256:
- 6965335e13458126fcfea659b55c886dd4a382b533f777b2d2b761038d210de1
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