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:
- 7ea536ee0ad78b8c4f4c665079dfb7a6c3f9fb4563ce18a7f104e044e50c82f0
- Size of remote file:
- 3.44 kB
- SHA256:
- 7ecc64f9876a4f0c346c3eb59050c316b02b718163e7bb396925cf0748ca9e0a
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