Text Classification
Transformers
PyTorch
English
camembert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/camembert-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/camembert-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/camembert-base-mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/camembert-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/camembert-base-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#2)
- Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (f5ce2f3639dfd63103f2ca40b9c807946e1111a1) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>6451b68
-
Add evaluation results on the mrpc config of glue (#1)
- Add evaluation results on the mrpc config of glue (7557aa8be1184804e3b6561d3fb7d9925b86b4a9) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>29c1e5f
-
upload fp32 model
39ba8cb -
initial commit
11f199d