Instructions to use alaggung/bart-r3f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alaggung/bart-r3f 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="alaggung/bart-r3f")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alaggung/bart-r3f") model = AutoModelForSeq2SeqLM.from_pretrained("alaggung/bart-r3f") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac6b0e5bf5e41a8ce6a2d224357eec1ace135666a506530f31ade863f994ac0f
- Size of remote file:
- 187 MB
- SHA256:
- 8bfac7caa7f00f0979cc27a2bc8aa5859735de79a0df6fed0a69b894418e2218
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