Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use exala-e/db_himp_4.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use exala-e/db_himp_4.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="exala-e/db_himp_4.2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("exala-e/db_himp_4.2") model = AutoModelForSequenceClassification.from_pretrained("exala-e/db_himp_4.2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 749a5262b6ed0f1ea660b8c4828a57c01ab1ad9e5dbe180aded423b6d460fc28
- Size of remote file:
- 5.27 kB
- SHA256:
- a04cf66020e10730add713e96ad56f5b08ededcbb1f0d98a14bc6a5d9b630190
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