Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Tirendaz/my_distilbert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tirendaz/my_distilbert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tirendaz/my_distilbert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tirendaz/my_distilbert_model") model = AutoModelForSequenceClassification.from_pretrained("Tirendaz/my_distilbert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#5 opened about 3 years ago
by
SFconvertbot
Librarian Bot: Add base_model information to model
#4 opened about 3 years ago
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librarian-bot
Adding `safetensors` variant of this model
#3 opened about 3 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot