Instructions to use mrm8488/bert-small2bert-small-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-small2bert-small-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-small2bert-small-finetuned-cnn_daily_mail-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
e928e95 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:e755e8e298879922430f97c16bb16b9c7f6602dfe2c0cd7958508ef797c73c6c
size 247150043
|