Instructions to use mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization 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="mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization: direct link, hf CLI and curl.
- Browser
- Download file 93.8 MB
-
https://huggingface.co/mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization/resolve/main/pytorch_model.bin
93.8 MB
- Xet hash:
- 5ab739d673e42cb48413cc8f555d2166050382bb16b2b567da927ceac2a329d3
- Size of remote file:
- 93.8 MB
- SHA256:
- 0db6945137885092d5c2eb915204187933a460c9baffc21481e56dc7b4fad8ae
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