Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
bert
emotion
Eval Results (legacy)
text-embeddings-inference
Instructions to use bhadresh-savani/bert-base-uncased-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bhadresh-savani/bert-base-uncased-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bhadresh-savani/bert-base-uncased-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bhadresh-savani/bert-base-uncased-emotion") model = AutoModelForSequenceClassification.from_pretrained("bhadresh-savani/bert-base-uncased-emotion", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bhadresh-savani/bert-base-uncased-emotion: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/bhadresh-savani/bert-base-uncased-emotion/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://bhadresh-savani/bert-base-uncased-emotion@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bhadresh-savani/bert-base-uncased-emotion/resolve/refs%2Fpr%2F2/pytorch_model.bin
438 MB
- Xet hash:
- d8f1157e4cbd33507c073f53fdbb16ca526fe495dc7e0634aa91df4a028281ed
- Size of remote file:
- 438 MB
- SHA256:
- ebbad817820bb5e11d0de06b06c41344dcee484903c510f9949aa783cf5f0b3b
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