Summarization
Transformers
Safetensors
English
bart
text2text-generation
abstractive
hybrid
multistep
Eval Results (legacy)
Instructions to use MikaSie/LegalBERT_BART_dependent_V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MikaSie/LegalBERT_BART_dependent_V1 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="MikaSie/LegalBERT_BART_dependent_V1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MikaSie/LegalBERT_BART_dependent_V1") model = AutoModelForSeq2SeqLM.from_pretrained("MikaSie/LegalBERT_BART_dependent_V1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 818aad39d7ec79e43a75c8cf796675d12ddf99833db2de064293eef7a8d81929
- Size of remote file:
- 5.18 kB
- SHA256:
- 362f5a193bff3ac14d166d54d3073eb7d4a79ae1472d4df7ac335e9b2c943d0d
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