Text Classification
Transformers
Safetensors
English
modernbert
central_bank_communication
central_bank
economics
hawkish
dovish
text-embeddings-inference
Instructions to use brjoey/CBSI-ModernBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brjoey/CBSI-ModernBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="brjoey/CBSI-ModernBERT-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("brjoey/CBSI-ModernBERT-base") model = AutoModelForSequenceClassification.from_pretrained("brjoey/CBSI-ModernBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from brjoey/CBSI-ModernBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/brjoey/CBSI-ModernBERT-base/resolve/main/optimizer.pt
- Command line
-
hf download hf://brjoey/CBSI-ModernBERT-base/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/brjoey/CBSI-ModernBERT-base/resolve/main/optimizer.pt
1.2 GB
- Xet hash:
- ad25105b7164b60d7b14e8db39f26cbdcf992f235f358f7ce145fd5c5e79e008
- Size of remote file:
- 1.2 GB
- SHA256:
- c6fde4e97d878333bfe30f0720a38a0ce15576e81bad0e153dc67b8878fc191a
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