Fill-Mask
Transformers
PyTorch
English
bart
text2text-generation
summarization
long context
custom_code
Instructions to use ccdv/lsg-bart-base-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccdv/lsg-bart-base-4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ccdv/lsg-bart-base-4096", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ccdv/lsg-bart-base-4096", trust_remote_code=True) model = AutoModelForSeq2SeqLM.from_pretrained("ccdv/lsg-bart-base-4096", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91242d626516be573ca92250aa8d3eeea96810da3f3ae2cca23d0fabff01b1d7
- Size of remote file:
- 578 MB
- SHA256:
- 846341901417061086a1539604133c238fc62e05b5ace694f6c755c15a3fe6b8
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