Text Classification
Transformers
TensorBoard
Safetensors
bert
sjy
categorical
Generated from Trainer
text-embeddings-inference
Instructions to use JaeHwanLim/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JaeHwanLim/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JaeHwanLim/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JaeHwanLim/model_output") model = AutoModelForSequenceClassification.from_pretrained("JaeHwanLim/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b89658ae326b3f2d2c00583ac69f8a2365f9790dd6572e8f1e8bc7dfb0e2fa9d
- Size of remote file:
- 5.18 kB
- SHA256:
- 64bdbf34e2452715098a0eeb505a7d47227f44c9dfe4d065ffbffeee493b2bbc
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