Instructions to use zedfum/arman-longformer-8k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zedfum/arman-longformer-8k 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="zedfum/arman-longformer-8k")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zedfum/arman-longformer-8k") model = AutoModelForSeq2SeqLM.from_pretrained("zedfum/arman-longformer-8k") - Notebooks
- Google Colab
- Kaggle
Model Card for Model arman-longformer-8k
This project use Longformer's attention mechanism to alireza7/ARMAN-MSR-persian-base in order to perform abstractive summarization on long documents. so new model can accept 8K tokens (rather than 512 tokens).it should be fine-tuned for summarization tasks.
converting code is available in github repository
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