Text Classification
Transformers
PyTorch
English
distilbert
emotion-classification
mental-health
multi-label
goemotions
Instructions to use Utkarsh64/huggingface_distilbert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Utkarsh64/huggingface_distilbert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Utkarsh64/huggingface_distilbert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Utkarsh64/huggingface_distilbert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Utkarsh64/huggingface_distilbert_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Utkarsh64/huggingface_distilbert_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Utkarsh64/huggingface_distilbert_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Utkarsh64/huggingface_distilbert_model/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- fc11d6e2b2303a1dcc54bcd1b3cfc6373645de3226cc6ffdfa2a69a162dd793e
- Size of remote file:
- 268 MB
- SHA256:
- b844b4253f4b7502efc99fa889584c27425d58bbfc82550d70f9259d60165c10
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