Instructions to use transformer3/H2-keywordextractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transformer3/H2-keywordextractor 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/H2-keywordextractor")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("transformer3/H2-keywordextractor") model = AutoModelForSeq2SeqLM.from_pretrained("transformer3/H2-keywordextractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6faf2c190697174e78a4d64687db48f43ac5fc345aaa734d8ed56a42d9495bd5
- Size of remote file:
- 1.63 GB
- SHA256:
- dc4457de378f58b6b87914e2524f9d6a1310f4681587acb167da18855c78b468
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