Text Classification
Transformers
TensorBoard
Safetensors
English
modernbert
quality-estimation
classification
binary-classification
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ymoslem/ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ymoslem/ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ymoslem/ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ymoslem/ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05") model = AutoModelForSequenceClassification.from_pretrained("ymoslem/ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
bb8ad2a | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c7ab0e4de65ca732b3a4220685e2bfef64431a370356831739997ffba284ce87
size 6097
|