Text Classification
Transformers
ONNX
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use MoritzLaurer/ModernBERT-base-zeroshot-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoritzLaurer/ModernBERT-base-zeroshot-v2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MoritzLaurer/ModernBERT-base-zeroshot-v2.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/ModernBERT-base-zeroshot-v2.0") model = AutoModelForSequenceClassification.from_pretrained("MoritzLaurer/ModernBERT-base-zeroshot-v2.0", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MoritzLaurer/ModernBERT-base-zeroshot-v2.0: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/MoritzLaurer/ModernBERT-base-zeroshot-v2.0/resolve/main/training_args.bin
- Command line
-
hf download hf://MoritzLaurer/ModernBERT-base-zeroshot-v2.0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MoritzLaurer/ModernBERT-base-zeroshot-v2.0/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 980afd4f197c38189476f21bc452ea4ff3df3b6346f13c9f05c65a1c0ec6b65d
- Size of remote file:
- 5.5 kB
- SHA256:
- d72c8f25e91427ca093fa732f9c6509282f9c7e61979115b1a67dc055fb65320
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