Instructions to use Feluda/Final_Fine_Tuned_Legal_Led with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Feluda/Final_Fine_Tuned_Legal_Led 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="Feluda/Final_Fine_Tuned_Legal_Led")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Feluda/Final_Fine_Tuned_Legal_Led") model = AutoModelForSeq2SeqLM.from_pretrained("Feluda/Final_Fine_Tuned_Legal_Led", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ec5cf055849b415e8c05110c99724a0da847da96fa2bc0c593c65551c006d7e
- Size of remote file:
- 4.22 kB
- SHA256:
- d6ccf756c366b79df393fe50d837ed07594ee7426c5401df0da03ada7f3113e2
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