Instructions to use ncoop57/bart-base-code-summarizer-java-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncoop57/bart-base-code-summarizer-java-v0 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="ncoop57/bart-base-code-summarizer-java-v0")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ncoop57/bart-base-code-summarizer-java-v0") model = AutoModelForSeq2SeqLM.from_pretrained("ncoop57/bart-base-code-summarizer-java-v0") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -0
config.json
CHANGED
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@@ -42,6 +42,7 @@
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"model_type": "bart",
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"no_repeat_ngram_size": 3,
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"normalize_before": false,
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"num_beams": 4,
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"num_hidden_layers": 6,
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"output_past": true,
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"model_type": "bart",
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"no_repeat_ngram_size": 3,
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"normalize_before": false,
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"normalize_embedding": true,
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"num_beams": 4,
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"num_hidden_layers": 6,
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"output_past": true,
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