Text Classification
Transformers
TensorBoard
Safetensors
bert
lsb_ais5
categorical
multi_label
10_class
Generated from Trainer
text-embeddings-inference
Instructions to use SBzz/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SBzz/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SBzz/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SBzz/model_output") model = AutoModelForSequenceClassification.from_pretrained("SBzz/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01dc647f5c47c80396d4a446086766645c6f8a6af57f2404266cd69dabac7e02
- Size of remote file:
- 436 MB
- SHA256:
- 2be86361a87d1023e767efeba57934b6ce47860d5cbddd02a2029988358ea469
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