Transformers
PyTorch
English
bart
text2text-generation
onprem
llm
ai
ml
llmops
postgresml
pgvector
vmware
tanzu
Instructions to use tanzuhuggingface/dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanzuhuggingface/dev with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tanzuhuggingface/dev") model = AutoModelForSeq2SeqLM.from_pretrained("tanzuhuggingface/dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0aca363447ff11a8ae3026196b1c60cb3d74a8098db683846f9718006600bfb
- Size of remote file:
- 1.22 GB
- SHA256:
- 496c990ac2dd97d5c175022ff0202e9db47bc6123eea3ba207a0de67cef60871
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