Instructions to use silmi224/led-risalah_data_v17_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use silmi224/led-risalah_data_v17_2 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="silmi224/led-risalah_data_v17_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("silmi224/led-risalah_data_v17_2") model = AutoModelForSeq2SeqLM.from_pretrained("silmi224/led-risalah_data_v17_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 260
Browse files
model.safetensors
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runs/Jul14_06-45-27_440e4b9c3897/events.out.tfevents.1720939528.440e4b9c3897.696.0
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