Text Classification
Transformers
TensorBoard
Safetensors
new
Generated from Trainer
custom_code
text-embeddings-inference
Instructions to use farshadafx/ModernBERT-Letter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use farshadafx/ModernBERT-Letter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="farshadafx/ModernBERT-Letter", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("farshadafx/ModernBERT-Letter", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c093444cff85d79dc3c7f7883e903f572066bb2bf64c491f50717bc4d4b1cb3f
- Size of remote file:
- 5.3 kB
- SHA256:
- b63b5845a2cc4449fe6a74892641c0948a0755ac2f40f84053fc8e89f2d655bb
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