Text Classification
Transformers
PyTorch
Safetensors
Chinese
bart
text2text-generation
fill-mask
Summarization
Chinese
CPT
BART
BERT
seq2seq
Instructions to use OpenMOSS-Team/cpt-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMOSS-Team/cpt-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OpenMOSS-Team/cpt-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("OpenMOSS-Team/cpt-large") model = AutoModelForSeq2SeqLM.from_pretrained("OpenMOSS-Team/cpt-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cd5d62ebdd280a12c8c5978d528efb237266298fcbebf14ad8fa85244191e2a
- Size of remote file:
- 1.7 GB
- SHA256:
- 5620a50d5b02e440efdc73c75cdd9a98b301bd12a67ef6f741806c3706c4661f
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