Text Classification
Transformers
PyTorch
TensorBoard
English
distilbert
qa-metrics
call-center
multi-head
transcript-analysis
customer-service
quality-assurance
child-helplines
crisis-support
social-impact
swahili
east-africa
Eval Results (legacy)
Instructions to use openchs/qa-helpline-distilbert-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openchs/qa-helpline-distilbert-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="openchs/qa-helpline-distilbert-v1")# Load model directly from transformers import AutoTokenizer, MultiHeadQAClassifier tokenizer = AutoTokenizer.from_pretrained("openchs/qa-helpline-distilbert-v1") model = MultiHeadQAClassifier.from_pretrained("openchs/qa-helpline-distilbert-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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