Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/emotion_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/emotion_trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/emotion_trained")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/emotion_trained") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/emotion_trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/emotion_trained: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/emotion_trained/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/emotion_trained/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/emotion_trained/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 83c50932ea70906cf90bf72a42582d4ae0232a6bcd90e759f78aa496250f90ad
- Size of remote file:
- 268 MB
- SHA256:
- cb52144fd2a404d31be91d192b867911f0e8b9057a0b5e9ad0139ffcc8c4ed75
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