Fill-Mask
Transformers
PyTorch
English
bart
text2text-generation
summarization
long context
custom_code
Instructions to use ccdv/lsg-bart-base-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccdv/lsg-bart-base-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ccdv/lsg-bart-base-16384", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ccdv/lsg-bart-base-16384", trust_remote_code=True) model = AutoModelForSeq2SeqLM.from_pretrained("ccdv/lsg-bart-base-16384", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5472b0d05428b993540938a0980ed09b8778de1e38b2857b684acf7b3c395b04
- Size of remote file:
- 654 MB
- SHA256:
- 59b245a42bcfbb05ef06ba4d22869ef375f1414d6138341c8d28b44ffaac27b1
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