Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use nouman-10/distilbert-base-uncased_intent_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nouman-10/distilbert-base-uncased_intent_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nouman-10/distilbert-base-uncased_intent_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nouman-10/distilbert-base-uncased_intent_classification") model = AutoModelForSequenceClassification.from_pretrained("nouman-10/distilbert-base-uncased_intent_classification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:17c5aa19865d7533edca02fbd329426d1735dfacb7427f8fb2b3893b8f45cb54
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size 267894088
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