Instructions to use mateiaassAI/MBERTbase_REDv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateiaassAI/MBERTbase_REDv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mateiaassAI/MBERTbase_REDv2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mateiaassAI/MBERTbase_REDv2") model = AutoModelForSequenceClassification.from_pretrained("mateiaassAI/MBERTbase_REDv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 376649d8e17ff5757610dbd194068e2cb9928b1c59468a461dacd9d1496882b6
- Size of remote file:
- 5.18 kB
- SHA256:
- f3c370178eb8e0120c65e36fee8b05adebf8a218a5a11a85ddf4228f21b9a230
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