Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use quesmed/emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quesmed/emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="quesmed/emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("quesmed/emotion") model = AutoModelForSequenceClassification.from_pretrained("quesmed/emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from quesmed/emotion: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/quesmed/emotion/resolve/main/training_args.bin
- Command line
-
hf download hf://quesmed/emotion/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/quesmed/emotion/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- b166b34efa69f30eaa8f3103f31a2f2c11201fe1b953f38b8198e7d8553d9de4
- Size of remote file:
- 4.03 kB
- SHA256:
- 7623ea64e49a2829e65aa74dd0819187ddeaac5449db9b5c083a0aafb8c50041
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