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:
- 29f8ea6bca1c559e79e2a0752cfffe3a6c9b2708b4077f70db33983899c2ae2f
- Size of remote file:
- 5.78 kB
- SHA256:
- e3e877c15d6a25253249492219000decddf8758f2ceb161727e3a1f18414fc1c
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