Text Classification
Transformers
TensorBoard
Safetensors
bert
sjy
categorical
multi_label
10_class
Generated from Trainer
text-embeddings-inference
Instructions to use JJeePP/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JJeePP/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JJeePP/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JJeePP/model_output") model = AutoModelForSequenceClassification.from_pretrained("JJeePP/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cc883b14aad7fc1ac7462102743a9e58d44b1b1c8a297d2425655db4828a864
- Size of remote file:
- 5.18 kB
- SHA256:
- 963e08f0a6e0c0690847cee1f18d90286ed43e1f247c017ea7ebaeabd4fb2337
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