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:
- 42f1201b8e79a7012bdb12b43e20827e1302d4c80e2f303b131085ad3251bcd7
- Size of remote file:
- 17.1 MB
- SHA256:
- 34d664f2f503439b686b70a15482dddaf9a590e65d8bf9ea2ca0addccecf7d21
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