Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Areepatw/bert-multirc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Areepatw/bert-multirc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Areepatw/bert-multirc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Areepatw/bert-multirc") model = AutoModelForSequenceClassification.from_pretrained("Areepatw/bert-multirc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a75018cd591ac048421f7c3bacf576ea7f086e8aad06cbe0ff490915aac37d63
- Size of remote file:
- 5.24 kB
- SHA256:
- eec0bcdb75d6f7cf1875b56e45baf915e577cbcc1c1a410027465f58e71b8f64
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