Text Classification
Transformers
TensorBoard
Safetensors
bert
LMH
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use audgns/1008model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use audgns/1008model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="audgns/1008model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("audgns/1008model") model = AutoModelForSequenceClassification.from_pretrained("audgns/1008model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ad8c4342c095bb1b6b0694a3ba2e05a41cacee2f6b73c66e4a40a3cc7efc099
- Size of remote file:
- 5.18 kB
- SHA256:
- 16157f51c89fcdee8b835479c2b9bcc89d376b22128391ce723b0e0789c7969e
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