Instructions to use m3hrdadfi/bert2bert-fa-wiki-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/bert2bert-fa-wiki-summary 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="m3hrdadfi/bert2bert-fa-wiki-summary")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/bert2bert-fa-wiki-summary") model = AutoModelForSeq2SeqLM.from_pretrained("m3hrdadfi/bert2bert-fa-wiki-summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a4309adea8f5d2e6333d242e585b4bdbf6c37d610972a13b07eef28b4d118eb
- Size of remote file:
- 1.42 GB
- SHA256:
- 24e19afc564875a35aa3230ffa9e577217a0a9eddcb47e459bb4648131d70d71
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.