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 pytorch_model.bin from Iftesha/miniLm-tuned-emotion: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/Iftesha/miniLm-tuned-emotion/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Iftesha/miniLm-tuned-emotion/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Iftesha/miniLm-tuned-emotion/resolve/main/pytorch_model.bin
134 MB
- Xet hash:
- 14724057835acdfc5449c3994604e97808a844cf42dc6f8a28790c943ea9f835
- Size of remote file:
- 134 MB
- SHA256:
- ec1816bb2e82f807ca80a733d38b2263d976acbc268ec9e5b1063d8092ec9769
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