Text Classification
Transformers
TensorBoard
Safetensors
bert
CYH
10class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use Jayzi/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jayzi/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jayzi/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jayzi/model_output") model = AutoModelForSequenceClassification.from_pretrained("Jayzi/model_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 204db576ee213c28ec3d2becbd5339ee3a951a5bdc5960849a8713c90af75051
- Size of remote file:
- 5.18 kB
- SHA256:
- 792700268024fda9a2ae2843596e2514601de69efe749f48c19b421c04120dff
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