Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use philschmid/bert-mini-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/bert-mini-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/bert-mini-sst2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/bert-mini-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("philschmid/bert-mini-sst2-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding ONNX file of this model
#4 opened over 1 year ago
by
xingfudezhongzi
Adding `safetensors` variant of this model
#3 opened almost 2 years ago
by
SFconvertbot
Librarian Bot: Update Hugging Face dataset ID
#2 opened over 2 years ago
by
librarian-bot
Librarian Bot: Add base_model information to model
#1 opened almost 3 years ago
by
librarian-bot