Text Classification
Transformers
Safetensors
distilbert
text-embeddings-inference
8-bit precision
bitsandbytes
Instructions to use jhonacmarvik/distilbert-command-classifier_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhonacmarvik/distilbert-command-classifier_quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jhonacmarvik/distilbert-command-classifier_quantized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jhonacmarvik/distilbert-command-classifier_quantized") model = AutoModelForSequenceClassification.from_pretrained("jhonacmarvik/distilbert-command-classifier_quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ead702365d08ff5fa505d16266e53a5709e1193d3e2abf967b19416c88945554
- Size of remote file:
- 91 MB
- SHA256:
- 8caceb2b894ea8a4c4a3cd40cbf90386e64dced62802f016f682cee2898673fe
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