Text Classification
Transformers
TensorBoard
Safetensors
bert
PKJ
10class
multilabel
Generated from Trainer
text-embeddings-inference
Instructions to use GUJO1/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GUJO1/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GUJO1/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GUJO1/model_output") model = AutoModelForSequenceClassification.from_pretrained("GUJO1/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a0f4d049c651bc1f1dd657c0ebf2488a78e03299bbdc6c19a252e6b87e0fb5d
- Size of remote file:
- 5.18 kB
- SHA256:
- 027d90487c8b65adcffb52115f690ac7fdcbef2e992d9d5bb8aa4d79028cf5d7
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