Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use JenLe/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JenLe/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JenLe/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JenLe/model_output") model = AutoModelForSequenceClassification.from_pretrained("JenLe/model_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd7cc953f99a98a3e96cd6ed6553b1cc05a067d781cdbe4c47e393ca2d5eaf65
- Size of remote file:
- 5.18 kB
- SHA256:
- beaa34204f2badd898d73b845447163c36387ee231ff6c92bb675ef2679dce40
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