Text Classification
Transformers
Safetensors
English
modernbert
intent-classification
banking
text-embeddings-inference
Instructions to use Ahmed167/modernbert-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed167/modernbert-banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmed167/modernbert-banking77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmed167/modernbert-banking77") model = AutoModelForSequenceClassification.from_pretrained("Ahmed167/modernbert-banking77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ahmed167/modernbert-banking77: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/Ahmed167/modernbert-banking77/resolve/main/training_args.bin
- Command line
-
hf download hf://Ahmed167/modernbert-banking77/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ahmed167/modernbert-banking77/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 06693b12c56b22c9600097afe7f7a73eb131a663472d883401f531e276abf20c
- Size of remote file:
- 5.2 kB
- SHA256:
- 253fda34b4e77b9e812e641ae4a872c66861b33c16fd1303beef855a7e624a3c
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