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:
- 646c905a4770c21083a598777305d0f6553d1a5fe509d1ba7844261d3cde6def
- Size of remote file:
- 2.11 MB
- SHA256:
- b555fe37d56c2064c5a5f35dea19fa77e48da5e81ccab2e4238577a87f324404
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