Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/bert-base-uncased-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/bert-base-uncased-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/bert-base-uncased-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/bert-base-uncased-mnli") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/bert-base-uncased-mnli") - Notebooks
- Google Colab
- Kaggle
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator
#2
by autoevaluator HF Staff - opened
Beep boop, I am a bot from Hugging Face's automatic model evaluator π! We've added a new verifyToken field to your evaluation results to verify that they are produced by the model evaluator. Accept this PR to ensure that your results remain listed as verified on the Hub leaderboard.
JeremiahZ changed pull request status to merged