Instructions to use ruanchaves/mdeberta-v3-base-porsimplessent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruanchaves/mdeberta-v3-base-porsimplessent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ruanchaves/mdeberta-v3-base-porsimplessent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ruanchaves/mdeberta-v3-base-porsimplessent") model = AutoModelForSequenceClassification.from_pretrained("ruanchaves/mdeberta-v3-base-porsimplessent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35032902117f139f332cdad8c7741f52a05b3d6963396426f91c7ca4d8bc1e49
- Size of remote file:
- 1.12 GB
- SHA256:
- 1a379f6cfe435eb9426e0a507e645377fcd1b1e7f42b6568ff73cee39e241e76
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