Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use WaRKiD/distilbert-base-uncased-finetuned-intel-llm-tf-dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WaRKiD/distilbert-base-uncased-finetuned-intel-llm-tf-dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="WaRKiD/distilbert-base-uncased-finetuned-intel-llm-tf-dataset")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("WaRKiD/distilbert-base-uncased-finetuned-intel-llm-tf-dataset") model = AutoModelForSequenceClassification.from_pretrained("WaRKiD/distilbert-base-uncased-finetuned-intel-llm-tf-dataset") - Notebooks
- Google Colab
- Kaggle
| { | |
| "[CLS]": 101, | |
| "[MASK]": 103, | |
| "[PAD]": 0, | |
| "[SEP]": 102, | |
| "[UNK]": 100 | |
| } | |