Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use Inabia-AI/modernBERT-large-claim-agent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Inabia-AI/modernBERT-large-claim-agent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Inabia-AI/modernBERT-large-claim-agent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Inabia-AI/modernBERT-large-claim-agent") model = AutoModelForSequenceClassification.from_pretrained("Inabia-AI/modernBERT-large-claim-agent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ab5048e1c24eb72df5f8cf47921f82e8b6310b1561d4761dee2e65c24cadd7d
- Size of remote file:
- 5.27 kB
- SHA256:
- 20e8e0e4c72192c5b2043ad7f784b9a9e836e3d5aa301bc95097f77521554a2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.