Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use philschmid/MiniLMv2-L6-H384-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/MiniLMv2-L6-H384-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/MiniLMv2-L6-H384-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/MiniLMv2-L6-H384-sst2") model = AutoModelForSequenceClassification.from_pretrained("philschmid/MiniLMv2-L6-H384-sst2") - Notebooks
- Google Colab
- Kaggle
Ctrl+K