Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use universalml/kjl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalml/kjl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="universalml/kjl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("universalml/kjl") model = AutoModelForSequenceClassification.from_pretrained("universalml/kjl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8acf30e74f9103934917ed09ec2297176df9f8ef56b13f25ee57d78993bb9292
- Size of remote file:
- 4.09 kB
- SHA256:
- 8847f43ff07bea9e9c7045cd3508c2574ca2b9691ef0b7362cee56d8a7fc7dba
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