Text Classification
Transformers
PyTorch
TensorBoard
data2vec-text
Generated from Trainer
Eval Results (legacy)
Instructions to use mrm8488/data2vec-text-base-finetuned-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/data2vec-text-base-finetuned-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/data2vec-text-base-finetuned-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/data2vec-text-base-finetuned-mnli") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/data2vec-text-base-finetuned-mnli") - Notebooks
- Google Colab
- Kaggle
Align label mapping with mnli config of glue dataset
#1
by lewtun HF Staff - opened
Hi there, your model is using a default label mapping. Accept this PR to align the label mapping with the mnli config of the glue dataset this model was trained on. This will enable your model to be evaluated by Hugging Face's automatic model evaluator
mrm8488 changed pull request status to merged