Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Iftesha/miniLm-tuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Iftesha/miniLm-tuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Iftesha/miniLm-tuned-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Iftesha/miniLm-tuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("Iftesha/miniLm-tuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Iftesha/miniLm-tuned-emotion: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/Iftesha/miniLm-tuned-emotion/resolve/main/training_args.bin
- Command line
-
hf download hf://Iftesha/miniLm-tuned-emotion/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Iftesha/miniLm-tuned-emotion/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 2643dc85067c731d74f682f854c038064374fb0be9c20c8a961eebeb98c294b7
- Size of remote file:
- 4.03 kB
- SHA256:
- 8f48a36e7ae4942ae8a897dc2a64b3c00dce28dc57977b9cb8785f465117e912
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