Instructions to use Shruti9756/G24_Legal_Summarization_simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shruti9756/G24_Legal_Summarization_simple 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="Shruti9756/G24_Legal_Summarization_simple")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Shruti9756/G24_Legal_Summarization_simple") model = AutoModelForSeq2SeqLM.from_pretrained("Shruti9756/G24_Legal_Summarization_simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d15f6ac3b9c6f0d7ca86a8727afa491f617201d2d57708a2b3b78e7589332906
- Size of remote file:
- 1.22 GB
- SHA256:
- 9f84c386536607c84a8214cd192004505e43c728e1647dc2141fa1230eb13241
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