Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use 0xcynyx/distilbert-base-uncased-finetuned-emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0xcynyx/distilbert-base-uncased-finetuned-emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="0xcynyx/distilbert-base-uncased-finetuned-emotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("0xcynyx/distilbert-base-uncased-finetuned-emotions") model = AutoModelForSequenceClassification.from_pretrained("0xcynyx/distilbert-base-uncased-finetuned-emotions") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3647a8d490dc35e1e9280fa944a3325c9db88f93c96d80be813e8ea84aa9562d
- Size of remote file:
- 4.92 kB
- SHA256:
- eb7f5301cd468c68c17c99d210bc0ec5eca4b6443fc66a80b6c363411fba8b50
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