Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use subinsss/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use subinsss/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="subinsss/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("subinsss/bert_model") model = AutoModelForSequenceClassification.from_pretrained("subinsss/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d37b1f451933a266747e1bf427e7bc14a5e1adc78ffc4aac11b6e9ac55c8f72
- Size of remote file:
- 5.3 kB
- SHA256:
- a0322b8a271622241f5c83736b6f93de598cd8bf621f1076b39be7b3e3f8761b
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