Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ActivationAI/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ActivationAI/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ActivationAI/distilbert-base-uncased-finetuned-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ActivationAI/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("ActivationAI/distilbert-base-uncased-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ActivationAI/distilbert-base-uncased-finetuned-emotion: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/ActivationAI/distilbert-base-uncased-finetuned-emotion/resolve/main/training_args.bin
- Command line
-
hf download hf://ActivationAI/distilbert-base-uncased-finetuned-emotion/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ActivationAI/distilbert-base-uncased-finetuned-emotion/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- bb181886a41063b83010ca30c92745c126ed64ba620f7300acf53c7cbc866dfb
- Size of remote file:
- 2.86 kB
- SHA256:
- f9f9ac81e65fc3e9650f82164326fb56093817c7dc4840e77d8ab8eab4a5ae2c
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