Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use gokuls/bert-tiny-Massive-intent-KD-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gokuls/bert-tiny-Massive-intent-KD-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gokuls/bert-tiny-Massive-intent-KD-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gokuls/bert-tiny-Massive-intent-KD-BERT") model = AutoModelForSequenceClassification.from_pretrained("gokuls/bert-tiny-Massive-intent-KD-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2d561a2a5b1747dc31d91d8a3f7d5cde4d636d559b86acb74fb4e13a4d3831b
- Size of remote file:
- 17.6 MB
- SHA256:
- 39ebfe6e7db4689ee87f5f0f1f255287bb09a6f1461bd7e36c21b2a1f93fb087
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