Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Emil7018/classifier-chapter4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Emil7018/classifier-chapter4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Emil7018/classifier-chapter4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Emil7018/classifier-chapter4") model = AutoModelForSequenceClassification.from_pretrained("Emil7018/classifier-chapter4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5537645c61e94c79c10ffa84b9a5a82576bdeee1305bb318e86e09799b6d39a0
- Size of remote file:
- 438 MB
- SHA256:
- 6f5014f5151ee47dc1322b001b67f4656fb7e89fde4ee9f1153fc01d818066a1
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