Fill-Mask
Transformers
PyTorch
French
mbart
text2text-generation
summarization
bart
long context
custom_code
Instructions to use ccdv/lsg-barthez-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccdv/lsg-barthez-4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ccdv/lsg-barthez-4096", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ccdv/lsg-barthez-4096", trust_remote_code=True) model = AutoModelForSeq2SeqLM.from_pretrained("ccdv/lsg-barthez-4096", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3a4e1d6a15dedfbeb7c2f8e8af8daecdc3ba00b2d00e05955855120bc072392
- Size of remote file:
- 578 MB
- SHA256:
- 6baea65e9a49a6c7d5e99b6622bc7da3af0da5e22c378953bd63eff2cb86390e
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